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Small Startup, Mid-Size Company, or Fortune 100? The Pros and Cons

Early in my career, I walked into a shared office space on my first day as a full stack software developer and sat down between the CTO and the CEO to get onboarded. There were four of us in total. Before the day was over, I received my first assignment.

This was one of the most formative—and most stressful—experiences of my professional life. In the decade since, I have worked at half a dozen companies including Fortune 100 firms, mid-size startups, and companies you’ve probably never heard of. I have also spoken with roughly a thousand developers at various stages of their careers.

Most engineers entering the field are obsessed with landing at Google, Meta, or Amazon. But those roles represent approximately 0.6 percent of software engineering positions. For most of us, the real choice is between a small startup, a mid-size company, and a large enterprise. Each comes with tradeoffs, and your experience will differ from mine. What follows is an honest account of what you might reasonably expect.

The Small Startup

Pros

Your work actually matters. A feature you build might determine whether the company closes its next funding round. You gain exposure to the full spectrum of the business, from deployment pipelines to sales and operations and everything in between. You wear many hats out of necessity. For engineers who want to grow quickly and understand how a product is built end to end, few environments move faster.

Cons

Everything is on fire, always. Work-life balance is difficult to maintain when every release feels critical. Priorities shift without warning and culture tends to reflect the personality of whoever has the most influence in a small room. Startups optimize for speed over craft which means engineers learn to move fast but don’t always learn to build well, and that gap can follow you into your next role.

The Mid-Size Company

Pros

“So this is how a real business works.” There is process, documentation, a quality assurance function, and some form of career structure. The team is large enough to offer a diversity of experience and perspective. Stability is a myth, especially nowadays, but it is considerably more predictable than an early-stage startup.

Cons

“So this is how a real business works?” Processes that enable quality also produce friction. Access controls, approval workflows, and cross-team dependencies slow things down. The career ladder exists but it might stop at senior engineer. Without significant organizational growth, your salary and title can plateau early.

The Large Enterprise

Pros

That badge on your LinkedIn profile just bought you credibility for the next five years. Compensation at this level can be meaningfully higher, particularly when equity is included. The career ladder is long and clearly defined. Engineering practices at mature organizations tend to be more rigorous, and a well-known employer carries market value in future job searches.

Cons

It’s slow. Technology stacks often lag industry trends by several years. Political dynamics shape advancement as much as technical ability does. Skill atrophy is a risk when you spend years on a narrow slice of a legacy system. You are now a small fish in a big pond and it will be harder to get noticed.

The Roadmap I Would Take If I Could Start Over

According to a recent Stack Overflow survey, 47 percent of professional developers work at companies with fewer than 100 employees. This may surprise you because social media is dominated by engineers who work at the most well known companies on the planet.

The path most engineers imagine for themselves and the path most engineers actually walk are two very different things.

If I could do it again, here’s the path I’d take: Start at a small company to build breadth and learn how a business works across functions. This also provides some room to experiment within different roles. Next, move to a mid-size organization with a clear goal of reaching a senior or leadership role. Making a lateral move is easier than trying to get up-leveled at the next company. Finally, target a more mature company where a leadership position opens the door to meaningful equity and long-term growth (aka stocks and bonuses).

Each stop builds something the others cannot. The startup gives you range. The mid-size company gives you a taste of how larger orgs operate. The enterprise gives you leverage, credibility and maybe even some stability.

Your path will not look like mine. At a five person startup, I had no idea what I was in for. Looking back, I would not trade it. Just know what you are signing up for before you sign.

—Brian

Reclaiming Social Engineering for Good

“Social engineering” is a concept that has become associated with phishing, in which scammers manipulate people into disclosing personal information. But shaping human behavior in this way doesn’t have to have such negative effects. Systems engineer Guru Madhavan argues that we need to reclaim the term and govern the practice to defend ourselves from bad actors and benefit from social engineering’s good side.

Read more here.

Get Your Medical Mobile App Verified by IEEE

Smartphone apps are increasingly used to help manage medical conditions, but many of these have not been verified by any regulatory agencies. To help ensure these apps are credible, the IEEE Standards Association recently launched a directory listing apps that have been vetted by experts for technical soundness, ethical design, data security and privacy, and clinical efficacy. The registry will be publically available at no cost, and developers can now apply for approval.

Read more here.

Finding Success in Industry as a Chip Designer

A veteran chip designer reflects on what he learned when moving from academia to industry, where the goal changes from proof of concept to ensuring a design works reliably at scale. Differences in risk tolerance, he discovered, lead to varying approaches in the rapidly growing semiconductor industry.

Read more here.

This article is crossposted from IEEE Spectrum’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free!

Job Hopping as an Engineer: The Pros and Cons

I’ve changed jobs more times than I ever imagined I would. In the past 12 years, I’ve worked at seven different organizations. Some of those moves were forced by layoffs. Others were deliberate bets on my own trajectory.

Job hopping, done strategically, is one of the fastest ways to accelerate your compensation and reinvent your professional identity. Engineers who understand when to move and when to stay tend to out-earn and out-rank their peers who simply wait for internal recognition.

Unfortunately, most engineers either job hop too much or not enough, and both mistakes are expensive. Here are the pros and cons of job hopping as an engineer, and when to make a leap.

Pro: It’s the fastest way to grow your salary

Internal raises and external offers operate on completely different logic, and most engineers don’t fully appreciate this until they make their first move.

Within a company, compensation is anchored to your existing salary and capped by organizational pay bands. A strong performance review might get you 5 to 8 percent.

An external offer is a clean slate. The company is bidding for your market value, not adjusting from your current baseline.

My first deliberate job hop doubled my salary in a single year. A later move, at the same job title, pushed my compensation floor to a level that I never would have reached by staying put. Neither outcome was available internally. The math simply does not work in your favor when you stay.

Pro: It lets you reinvent yourself

Every new company is a chance to walk in as a slightly updated version of yourself: the version that learned something from the last place. The version that does not carry the baggage of whatever decision you made two years ago that all your coworkers still remember.

Especially when you’re early in your career, this matters. You get to reframe your experience, take on a different scope, and establish a new reputation from scratch. That kind of reset is difficult to manufacture inside the same organization.

Con: You don’t see the long-term outcome of your work

This is the part nobody talks about, and it took me years to fully appreciate it.

When I joined one company, I built a component library for a website from scratch. Starting projects from scratch is exciting, and the initial implementation held up well for the early use cases. But as the organization scaled, the limitations of my original design became apparent.

I stayed long enough to address them rather than handing that problem to someone else. That experience taught me more about software architecture than any new project ever had.

Engineers who move every 18 months only ever experience the exciting part of building something. They never experience the part where their original decisions stop working. They just repeat the exciting part on a loop, never realizing the debt they are leaving behind.

Con: You cannot job hop your way to a promotion

Above a certain level, things can change significantly.

A new employer can evaluate your past performance through interviews, portfolios, and references. What they cannot do is evaluate your future potential the way a manager who has watched you grow over two or three years can. If you arrive as a senior engineer, you will almost certainly be hired as one.

The promotions that actually changed my career trajectory—from senior to staff engineer, then engineering manager—all happened at one organization over four years. Those transitions required someone to observe my growth over time and make a bet on where I was headed next. That kind of credibility cannot be transferred on a resume.

So when should you actually leave?

The threshold I use is straightforward. If I have produced at least one measurable, clearly definable outcome at an organization, I have a reasonable basis for leaving. Impact, not tenure, is my unit of measure.

I personally think that moving deliberately while early in your career will build a strong compensation baseline.

Then become selective.

Find an environment where real growth is available and stay long enough to build the credibility that job hopping cannot manufacture. Neither constant movement nor blind loyalty is the answer. The question worth asking at every stage is simple: Have I produced something meaningful here yet? If the answer is no, stay. If yes, it might be time to decide what’s next.

—Brian

The USC Professor Who Pioneered Socially Assistive Robotics

What if robots didn’t just help us with physical tasks? USC Professor Maja Matarić helped define the era of socially assistive robotics, designed to provide personalized therapy and care through social interactions. Despite her influence in the field now, the award-winning roboticist didn’t see herself as an engineer at first.

Read more here.

Steve Jobs’ Wilderness Years Shaped His Success as Apple CEO

Steve Jobs is best known as the co-founder and CEO of Apple. But the 12 years he spent away from the company taught him the lessons necessary for his success. A new book tells the forgotten story of Jobs’ “wilderness” years and what he learned while at NeXT Computer. IEEE Spectrum spoke to the book’s author about Apple’s most iconic CEO and the company’s future as it prepares for new leadership under John Ternus.

Read more here.

Learn What It Takes to Become a Cybersecurity Consultant

Cybersecurity consultants have never been more in demand, with data breaches and attacks costing organizations more than US $10 trillion annually to repair. To help you find the skills you need to stand out in the cybersecurity job market, the IEEE Computer Society offers a “What Makes a Great Cybersecurity Consultant” guide. It includes advice from experts, a list of certifications to pursue, and information on key cybersecurity conferences.

Read more here.

This article is crossposted from IEEE Spectrum’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free!

The CS Degree Isn’t Dead. The Entry-Level Pipeline Is

There is no shortage of people telling recent engineering graduates that their degree was a mistake and that AI is coming for their jobs before they even land one. I respectfully disagree.

I have been a software engineer for 12 years, done well over 100 interviews on both sides of the table, and run Parsity, an AI engineering program. A few patterns emerge consistently in who actually breaks through in today’s job market. Here’s why I think the job market isn’t as dire as it looks, and what I would do if I were looking for my first tech job.

The Numbers Need Context

The Federal Reserve Bank of New York recently placed unemployment for recent CS graduates in the United States at 6.1 percent, with computer engineering graduates at 7.5 percent. Compared to philosophy majors at 3.2 percent and art history graduates at 3.0 percent, those figures look alarming. They require more context than most headlines provide.

When researchers factor in underemployment (graduates working jobs that don’t require a college degree), then engineers are doing relatively well, coming in below 20 percent, against a 42 percent average across all recent graduates. Many majors reporting lower unemployment are achieving that figure by accepting work entirely unrelated to their field. Scored across unemployment, underemployment, and early-career earnings together, CS and computer engineering still rank among the top fields for overall labor market outcomes.

The degree is not the problem. The hiring pipeline is. Job postings labeled “entry-level software engineer” grew roughly 47 percent between late 2023 and late 2024, while actual hiring into those roles dropped approximately 73 percent in the same window. So-called “ghost jobs,” used to create an illusion of company growth, are everywhere. This makes the front door harder to find, but it exists.

Here Is What To Do About It

Do a broad search of your (real-life) network. Roughly 26 percent of job offers come through referrals. Look at your actual network—classmates, professors, past internship contacts, relatives—and identify people at companies that might be hiring. The goal is a warm introduction to someone who is or knows a decision maker. One introduction carries more weight than a hundred cold applications through a portal.

Find symmetric risk. A junior engineer is a risky hire by definition. A startup carries a matching risk profile, meaning potentially lower compensation, no certainty of longevity, and higher performance expectations. But that shared risk creates mutual interest. The learning curve is steep, the exposure is broad, and the track record transfers directly. For engineers whose longer-term goal is a large organization, a startup is not a detour. It can be how you build the experience those organizations eventually want to see. The first job is for validation and learning. It is not a life sentence.

Manufacture experience rather than waiting for it. Employers want experience but will not hire you to get it. The way through is to create it: a deployed project, an open-source contribution, building something real for a small business or family member. Recruiters are skeptical of toy projects. A deployed application solving a real problem, combined with the ability to talk clearly about the decisions you made and why, still moves the needle.

Gain practical AI engineering skills, not just AI tool fluency. Using Cursor or Copilot is now a baseline expectation. What differentiates candidates is going one level deeper. Most working engineers, including senior ones, have not built a RAG pipeline or designed a multi-agent system. Understanding how to chunk documents, generate embeddings, store and query them from a vector database, and wire it into a production application puts a candidate ahead of a significant portion of the market on a skill in rapidly growing demand. AI and data science roles grew 163 percent in job postings in 2025. The engineers who understand how these systems actually work, not just how to prompt them, are in the shortest supply.

Stop optimizing around conditions you cannot predict. Nobody anticipated the 2021 hiring boom. Nobody predicted this correction. Build durable skills. The demand for engineers who can reason clearly about systems is not going away. Where you start is not where you end.

—Brian

Meta and Microsoft have joined the layoff tsunami. Is AI really to blame?

More major workforce reductions are on the horizon at Big Tech companies: Meta announced it will cut 10 percent of its workforce, or about 8,000 employees, and Microsoft plans to offer buyouts for 7 percent of its U.S. employees in a voluntary retirement program. The cuts are understood by many to be linked to AI. But is AI really to blame? For The Conversation, two academics at the University of Sydney give their two cents.

Read more here.

This Roboticist-Turned-Teacher Built a Life-Size Replica of ENIAC

Tom Burick got his start as a roboticist. But when a financial downturn forced him to close his robotics business, he thought of the effect teachers had on his life and decided to pay it forward. Burick now works as a technology instructor at a school for students with autism, where he recently led a project building a full-scale replica of ENIAC, an historic computer celebrating its 80th anniversary this year.

Read more here.

Proposed Chinese Robot Ban is Latest U.S. Tech Sovereignty Move

Across several industries, the United States has been moving toward limiting the use of sensitive technology made in China. Now, legislation has been introduced to extend the trend to ground robots, including humanoids, dogs, and crawlers. This could benefit some U.S.-based robotics firms—but many of these companies still rely on Chinese-made components. “The U.S. robotics industry is in a pickle,” writes Spectrum tech policy editor Lucas Laursen.

Read more here.

New York City was the backdrop of this year’s IEEE Honors Ceremony, held on 24 April.

The event celebrates engineering pioneers who have developed technologies that have changed how people connect and learn about the world. This year’s celebrants included the engineers behind innovations such as text-to-donate technology, AI-powered diagnostic tools, and the graphics processing unit, among many others.

Prior to the Honors Ceremony, IEEE hosted a forum on 23 April for a select group of early-career achievers to exchange ideas and experiences with laureates and awardees, speakers, and IEEE leaders. Attendees from around the world, working in a variety of technical areas, shared their journeys and explored the intersections of technologies, disciplines, and missions.

The event culminated in Friday evening’s black tie Honors Ceremony, where IEEE celebrated medal laureates, including Jensen Huang, who received IEEE’s highest recognition, the IEEE Medal of Honor. Huang is a cofounder of Nvidia and its chief executive.

“IEEE has always been a home to those who see the future before others see it,” Mary Ellen Randall, IEEE president and CEO, said in her welcome speech.

Video highlights and photos from the event are available on the IEEE Awards website.

Exploring mission-driven tech and AI in art

Friday morning began with a conversation between Randall and Marian Croak, the recipient of this year’s IEEE Founders Medal. Croak was honored for “leadership in communication networks, including acceleration of digital equity, responsible artificial intelligence, and the promotion of diversity and inclusion.”

Croak, who serves as vice president of engineering at Google, headquartered in Mountain View, Calif., pioneered Voice over Internet Protocol (VoIP) technologies. When a person speaks into a telephone, VoIP converts their voice into digital signals that are transmitted over the Internet rather than traditional phone lines. Her work enabled audio and video conferencing. She also developed text-to-donate technology to raise money for those affected by Hurricane Katrina, which devastated New Orleans in 2005. The technology enables customers to donate money to a charity via their mobile service provider, which then bills them.

“Empathy has always been a driving force in the engineering that I’ve done,” she said.

She shared advice on how to stay creative: “Get out of the office. Go to an art museum, exercise, or play with children.” Croak said her grandchildren inspire her.

An inside look at microchips

During Friday evening’s Honors Ceremony cocktail hour, attendees explored the history of microchips at the IEEE Global Museum’s Microchips That Shook the World exhibit. The Global Museum, an IEEE History and Heritage program, develops traveling and digital exhibits focused on the history of technology. The museum’s mission is to promote awareness of how technological progress unfolds over generations and how engineers and researchers build on past achievements to benefit humanity.

Drawing from IEEE Spectrum’s Chip Hall of Fame, the Microchips That Shook the World exhibit conveys the roles integrated circuits play in fields such as signal processing, audio engineering, and telecommunications.

Co-curators Stephen Cass, Spectrum’s special projects editor, and Daniel Mitchell, the IEEE senior historian, served as onsite docents for guests. The Commodore 64, one of the artifacts on display, brought up many treasured childhood memories for guests who used the home computer. The exhibit also featured a preview of IEEE’s immersive video project “Inside the Microchip,” which delves beneath the silicon surface of the Nvidia NV20 microchip thanks to forensic photography and sophisticated computer-generated renders. The video, which will be released later this year, aims to teach preuniversity students about the technology.

The daytime program also spotlighted AI’s use in the visual arts. Kathleen Kramer, the 2025 IEEE president, interviewed artist Refik Anadol, who is scheduled to open an AI art museum on 20 June in Los Angeles. Dataland’s exhibits are powered by an open-access model developed by Anadol’s studio.

For the museum’s first exhibition, “Machine Dreams: Rainforest,” the model collected visual data about the natural world from the Smithsonian National Museum of Natural History, London’s Natural History Museum, and the Cornell Lab of Ornithology, with their permission. The information, including up to a half billion images, will form the basis for a variety of AI-produced art, Anadol said.

Anadol said he was inspired to mix AI with art by the movie Blade Runner. He said he believes “machines can become collaborators,” as “data is a form of pigment.”

Data also plays an important role in the work of artist and author Giorgia Lupi. The artist is a partner at design firm Pentagram.

Lupi said she uses data to tell stories, including chronicling her struggles with a chronic illness.

“Data is an abstraction of our reality,” she said.

One of her recent projects, “A Data Love Letter to the Subway,” was shown last year in the Dey Street Passageway in New York City. The video was made using data from the Metropolitan Transportation Authority about each train line, including timetables, ridership, and people’s travel habits. Based on the information Lupi gathered, she documented how commuters traveling on different subway lines encountered one another without realizing it.

By exploring data on this year’s IEEE award recipients, she collaborated with IEEE to create an animated video illustrating the shared pathways and collaborations among the honorees. It debuted at the Honors Ceremony.

Honoring engineering giants

The Honors Ceremony, held at Cipriani 42nd Street, recognized more than 20 laureates and innovators.

More than 92 million selfies are taken worldwide every day, PhotoAiD estimates. A selfie wouldn’t be possible without Eric Fossum’s invention of the CMOS image sensor. Developed at NASA’s Jet Propulsion Laboratory, in Pasadena, Calif., the “camera on a chip” was intended for use in space, but it is now found in smartphones, medical devices, and vehicles. Fossum, an IEEE Life Fellow, received the IEEE Jun-ichi Nishizawa Medal, which recognizes outstanding contributions to materials and device science and technology.

“Engineering is a pursuit of what must be possible. [IEEE is] the spirit, the conscience, of our profession.” —Jensen Huang, founder and CEO of Nvidia

The medal, he said, “is at the top of the IEEE staircase of being recognized by your peers.”

The IEEE Holonyak Medal for Semiconductor Optoelectronic Technologies went to Steven P. DenBaars, a professor of materials and electrical and computer engineering at the University of California, Santa Barbara. DenBaars was honored for his work in semiconductors, which laid the foundation for high-resolution LED and laser displays, modern solid-state lighting, and more.

“This work has always been a team effort...I’m excited and curious about the role gallium nitride micro LEDs will play in optical communications,” he said in his acceptance speech.

The ceremony ended with the Medal of Honor presentation to Huang, who received a standing ovation. He was recognized for his “leadership in the development of graphics processing units and their application to scientific computing and artificial intelligence.”

The IEEE honorary member donated his cash prize to IEEE TryEngineering, which provides teachers with a library of lesson plans and offers educational summer camps. The Jen-Hsun and Lori Huang Foundation matched his gift, and the additional donation is destined to fund scholarships for new graduates.

“Engineering is a pursuit of what must be possible. [IEEE is] the spirit, the conscience, of our profession,” Huang said.

New graduates’ careers are unfolding in an era when AI is not optional. The most successful engineers treat artificial intelligence as leverage, not competition.

Here are seven tips to help keep young professionals in demand no matter how quickly the field’s tools evolve.

1. Master the fundamentals first. AI tools can help you code, but you still need strong fundamentals in:

• Data structures and algorithms for problem-solving.
• Operating systems, databases, and networking for system-level understanding.
• Core programming languages such as C++, Java, and Python.

AI can autocomplete syntax, but if you don’t understand how things work under the hood, you’re likely to struggle to debug or optimize.

2. Learn how to work with AI, not against it. The best engineers will not try to out-code AI. Instead, they will learn to:

• Write clear prompts to generate better code snippets.
• Review and debug AI-generated code for accuracy, performance, and security.
• Use AI for productivity boosts while still exercising judgment.

Think of AI as a teammate. The real skill is knowing when to trust it and when not to.

3. Build projects that showcase end-to-end thinking. Employers increasingly look for engineers who can design and build systems, not just solve problems. Create projects that show you can:

• Define requirements clearly.
• Use AI tools responsibly within the workflow.
• Deliver a product that scales and is maintainable.

4. Sharpen your system design skills early. Even junior engineers are now asked questions about basic system design with AI. Expect to explain to prospective employers:

• How you would responsibly integrate AI into a system.
• How to design fallbacks when AI fails.
• How to ensure scalability and reliability.

5. Develop strong communication skills. Today’s engineers don’t just code in isolation. You will be expected to:

• Explain design choices to teammates and stakeholders.
• Document decisions clearly.
• Collaborate effectively in cross-functional teams.

This is one area where AI cannot replace you. Clear communication is a career accelerant.

6. Stay curious and keep learning. The tech industry moves fast, and AI is accelerating that pace. Cultivate habits such as:

• Following industry news, blogs, and open-source projects.
• Experimenting with new AI tools, frameworks, and libraries.
• Engaging in communities such as GitHub, IEEE Collabratec, LinkedIn, and Medium.

Employers value engineers who keep themselves sharp and relevant.

7. Think beyond coding. AI will increasingly handle routine coding tasks. The differentiators for you will be:

• Problem-framing: Can you take a vague idea and turn it into a solution?
• Architectural judgment: Can you design systems that scale and last?
• Ethical awareness: Can you spot risks in AI use and address them responsibly?

For more career advice, subscribe to the IEEE Spectrum Career Alert Newsletter. The biweekly newsletter features the latest information on jobs, education, management, and the engineering workplace.

I have been an application-specific IC (ASIC) designer for almost three decades. Over that time, I’ve moved through the full academic trajectory, from graduate student to full professor; later, I transitioned to industry after an unsuccessful stint at entrepreneurship. When I made the switch to the private sector in 2019, I began focusing on a critically important aspect of the electronic industry: silicon intellectual property.

As much as 80 percent of the physical area in today’s most advanced chips is occupied by blocks that aren’t made for specific products or even designed by the consumer-facing companies that built them. Instead, chipmakers draw heavily on established silicon IP from companies like Arm, Cadence, Rambus, Synopsys, and the company I work for, Silicon Creations.

Throughout my career, I’ve designed chips for very different purposes, including enabling the research program in my academic lab and expanding the IP portfolio of my company. When I joined Silicon Creations, I had no idea how differently the industry approaches IC design and encountered a steep learning curve. Initially, it seemed that much of my two decades of academic research and training did not directly translate to the role. I had to learn new skills and adopt a new mindset.

Today, demand for ASICs is rapidly growing, driven by the need for specialized chips in the automotive sector, AI applications, and more. By one market estimate, the ASIC market is expected to grow from US $23.4 billion to $38.8 billion by 2033, and the semiconductor industry as a whole is projected to hit $1 trillion by 2030. The industry needs more chip designers—but if you’re coming from an academic background as I did, there are a few things you’ll need to know.

Different goals lead to different strategies

The differences between industry and academe begin with a divergence in purpose. In academia, my primary objective was to generate new knowledge: to propose a novel circuit technique, validate an unconventional architecture, or explore the limits of performance in a given domain. A successful chip is one that demonstrates a concept. In industry, it is not nearly enough to prove that something can work. The goal is to ensure that it works reliably, repeatedly, and at scale. Success is measured not by novelty but by whether the silicon meets specifications, yields as expected in production, and supports a competitive product delivered on schedule.

This leads to a stark contrast in risk tolerance. Academic designs often deliberately push into unproven territory, where even partial success can yield valuable insight. In industry, however, we systematically minimize risk. The cost of failure makes first-time silicon success a central requirement—especially at advanced technology nodes, where the lithography masks used to transfer circuit designs onto silicon wafers alone can cost tens of millions of dollars. As a result, industry design flows are built around eliminating uncertainty through conservative margins, extensive validation, and careful reuse of proven solutions.

“Academia explores the design space, asking what is possible, while industry exploits it, determining what is viable at scale.”

This paradigm has existed since the 1970s, when application-specific chip design was established. However, the gulf between academia and industry has expanded since the mid-2010s, when FinFET technology, a 3D architecture using vertical “fins” of silicon, was widely adopted in industry. System designs are also becoming increasingly modular with the advent of chiplets. This fundamentally altered the economics and complexity of ASIC development, with design costs rising by almost an order of magnitude. Initiatives like Taiwan Semiconductor Manufacturing Co.’s University FinFET Program and new government-funded chip-design hubs now let some well-resourced universities design for more advanced architectures, but the technology is still out of reach for many academics.

What the industry-academia split means in practice

Consider a startup developing an ASIC. Its engineering team may have deep expertise in a particular algorithm, sensor interface, or system architecture, the features that define its competitive advantage. But it is unlikely to possess world-class expertise in every supporting function. Developing each of these blocks internally would require significant time, capital, and specialized talent. Doing so could delay market entry beyond the startup’s viability.

Even large semiconductor companies face similar constraints. Advanced-node development demands intense focus. Allocating a team to redesign a standard interface block that has already been implemented elsewhere may be difficult to justify when differentiation lies at the system level, such as an inference chip’s ability to speed up neural network computations. The time it takes to move a new chip from conception to market and risk mitigation, not self-sufficiency, govern most decisions about in-house development versus outsourcing.

The economics of advanced IC manufacturing reinforce this reality. When the development cost of a leading-edge chip reaches hundreds of millions of dollars, minimizing risk becomes a central design imperative.

In this context, silicon IP emerged as a practical solution. Similar to how software developers rely on preexisting libraries rather than writing every function from scratch, ASIC designers license predesigned, preverified silicon blocks—such as processor cores, memory interfaces, and security engines—from highly specialized IP vendors. These blocks can then be integrated into larger, increasingly complex systems.

Design scope, verification, and time horizons

With the use of silicon IP, industry is able to widen the scope of its designs. Academic efforts tend to focus on block-level innovation: a new analog-to-digital converter architecture or an ultralow-noise amplifier, for instance. These designs typically abstract away many of the complexities of bringing a chip to market, such as packaging constraints, long-term reliability, and manufacturing yield.

In industry, the focus shifts to system-level integration. Modern systems on chips, or SoCs, incorporate dozens or even hundreds of functional blocks. Managing signal integrity, timing, firmware interaction, and system-level validation becomes as critical as the design of any individual block.

Verification philosophy also diverges sharply. In academia, the goal of verification is to demonstrate that the concept works under nominal conditions, which may not always reflect how it would perform in real applications. Even if only a fraction of fabricated chips from a multiproject wafer operates correctly, the design may still be considered a success if it validates the underlying idea.

At my academic lab for instance, we used to receive 40 chips from a TSMC prototyping service and started testing them in batches of five. If the first five or 10 chips proved functional, we had already collected more than enough data for a publication. If some of them failed, we weren’t required to mention this when publishing the results.

In industry, verification is exhaustive, critical, and often dominates the development schedule. Failures are measured in parts per million, and even rare anomalies are carefully analyzed and documented to identify root causes and prevent recurrence. When I started at Silicon Creations, I was surprised by the level of detail and scrutiny designs face.

Differences in time horizons and economic constraints reinforce each of these contrasts. Academic projects operate on flexible timelines aligned with research and funding cycles. If I missed a deadline, I just had to wait for the next cycle. Industry projects are driven by fixed product schedules and market windows, frequently targeting costly leading-edge nodes to achieve competitive performance, power, and area efficiency. Missing a deadline can negate the value of an entire design and may have major financial consequences along the entire supply chain.

In essence, academia explores the design space, asking what is possible, while industry exploits it, determining what is viable at scale. Both are indispensable, but they operate under fundamentally different definitions of success. As ASIC complexity continues to grow, understanding both perspectives will be essential for the next generation of engineers navigating the evolving semiconductor landscape.

This article appears in the June 2026 print issue.

The OnCampus program, administered by IEEE Educational Activities, last year expanded its engineering experiences from two to seven universities.

Part of TryEngineering, the program is held at universities around the world, offering preuniversity students hands-on opportunities to solve engineering problems.

The IEEE Innovation Committee provided funding for the additional locations.

New participating institutions

The electrical engineering and computing faculty at the University of Zagreb, in Croatia, hosted a two-day program in June. Twenty-five children ages 10 to 14 participated in lectures and workshops on artificial intelligence, computer science, robotics, and astronomy. Tomislav Jagušt, an IEEE senior member and the chair of the IEEE preuniversity coordinating committee, led the program.

In September the Arab Academy for Science, Technology, and Maritime Transport’s engineering college held a two-day session at its Abu Kir, Egypt, campus. Fifty students participated in hands-on activities on Ohm’s law, radio communications, and circuit building. They also learned from professors about engineering careers and job opportunities.

Also in September, the Majan University College, in Muscat, Oman, hosted 40 high school students who competed in six challenges to design and build circuits. These include an IoT design and an LED brightness control using a potentiometer, a three-terminal, manually adjustable resistor that functions as a variable voltage divider.

The program also highlighted AI and quantum computing technologies and introduced students to job opportunities in the fields.

The workshop transformed curiosity into creation, empowering students with technical skills and confidence in emerging technologies.

In November at the Universiti Malaysia Perlis, in Arau, 50 students explored the fundamentals of quantum computational intelligence and AI through hands-on activities and interactive simulations. IEEE Senior Member Mohd Hafiz Ismail, a professor of electronic engineering and technology, gave an introduction about quantum computing intelligence technology.

The Hellenic Robotics Center of Excellence at the National Technical University of Athens hosted a two-day session in December. Twenty-five students explored robotics and AI through hands-on design challenges such as TryEngineering’s AI and machine learning methods. They also toured the university’s research facilities.

Hong Kong and Greek universities participate again

The City University and St. Francis University in Hong Kong, and the University of Ioannina, Arta campus, Greece, participated in the program for a second year.

Under the leadership of IEEE Senior Member Paulina Chan and volunteers from the IEEE Hong Kong Section, the City and St. Francis universities jointly held the program in July. They welcomed 55 students ages 12 to 18 from 41 schools.

The students attended tutorials on foundational concepts and theories of AI. They worked in small teams on projects using AI-generated images, voice, and music manipulations. They were coached by students from St. Francis and Imperial College London. The participants presented their projects to judges, teachers, and parents.

The students also visited a nearby semiconductor equipment manufacturer to learn about technology careers from engineers working there.

The results of a post-program survey showed strong satisfaction with OnCampus, with nearly 75 percent of participants giving it a rating of 4 or higher out of 5.

“I enjoyed getting to know about deep learning and its application,” one student participant said. “The content of the activity matched my interest, and I gained new knowledge.”

“OnCampus is led by a strong team with lots of experts in the field,” another said. “It’s a rare chance for students to use software, learn about the theory behind how deep learning works, and get a glance at future possibilities.”

The University of Ioannina hosted the program in Arta in July with support from IEEE Senior Member Stamatis Dragoumanos and IEEE members Nikos Giannakeas and Eleftheria Kallinikou. Nearly 50 students, ages 12 to 16, attended the seven-day event, supported by 17 instructors and six volunteers from the university’s IEEE student branch.

The students learned about AI, augmented reality, microchip design, microcontrollers, and 3D printing. They also attended presentations by engineers from the industry. To give the students exposure to real-world engineering, they visited two hydroelectric power plants and a green data center.

At the end of the program, students presented their projects and showcased the technical skills they had developed.

Those involved in the TryEngineering OnCampus program are proud of the impactful experiences students have gained. The opportunities are possible because universities open their doors, share their expertise, and invest in the next generation of innovators.

The University of Zagreb, the Arab Academy for Science, Technology, and Maritime Transport, the Majan University College, and The City University and St. Francis University will be participating again this year.

The IEEE Communications Society (ComSoc)’s Research Collaboration Pitch Session initiative is proving to be a catalyst for meaningful engagement between academic researchers and industry innovators. Launched last year, the program connects promising researchers with industry leaders who can offer them funding, mentorship, and connections to bring interesting ideas closer to real-world deployment.

Rather than relying on chance encounters at conferences, the pitch sessions create a focused environment. Five academic presenters share their work with five industry representatives, known as “innovation scouts”: senior leaders primarily chosen from ComSoc’s Corporate Program partner companies such as Ericsson, Intel, Keysight, and Nokia. The curated format ensures that each idea receives dedicated attention from professionals who are seeking new concepts aligned with their organization’s priorities.

The initiative was launched in November at the IEEE Middle East Conference on Communications and Networking (MECOM) in Cairo and appeared in December at the IEEE Global Communications Conference (GLOBECOM) in Taipei, Taiwan.

AI-driven communication network

One of the most compelling outcomes came from the inaugural session in Cairo. Angela Waithaka, a student member and biomedical engineering student at Kenyatta University, in Nairobi, Kenya, presented her “AI-Driven Predictive Communication Networks for Enhanced Performance in Resource-Constrained Environments” paper. You can view her presentation along with others on IEEE.tv.

Waithaka’s research tackles a critical challenge: Next-generation communication systems increasingly rely on artificial intelligence and machine learning, yet most existing architectures consume abundant computational and energy resources, which are not always present in developing regions.

Waithaka proposed lightweight, adaptive AI/machine learning models capable of delivering predictive, reliable communication performance even under tight resource constraints.

Her vision resonated with Ruiqi “Richie” Liu, a master researcher at ZTE in China. ZTE is a global leader in integrated information and communication technology solutions. Liu says he recognized the relevance Waithaka’s proposal had to his company’s work with the International Telecommunication Union. He invited her to establish an ITU account so she could participate in the organization’s meetings discussing global telecommunications standardization projects—which would elevate her work to an international stage.

Simplifying data center protocols

The momentum continued at GLOBECOM. Among the presenters was Nirmala Shenoy, a professor at the Rochester Institute of Technology, in New York. Shenoy, an IEEE member, spoke on the topic of simplifying data center network protocols. She highlighted the growing complexity of the critical networks, which underpin cloud services, enterprise IT, and emerging AI workloads.

Shenoy’s focus on reducing protocol complexity while maintaining scalability, resilience, and low latency caught the attention of an innovation scout from Nokia, who heads its eXtended Reality Lab in Madrid. He found the key person at Nokia for Shenoy to connect with to discuss her research, and it led her to record a video for the company detailing her approach and its potential applications.

A model for accelerating innovation

The early success stories demonstrate the power of intentional, structured engagement. By bringing researchers and industry leaders together in a format designed for discovery, ComSoc is helping accelerate innovation and expand opportunities for collaboration. The pitch sessions are not merely conference events; they are becoming a bridge between academic creativity and industry implementation.

This year sessions will be held during the IEEE International Conference on Communications in Glasgow from 24 to 28 May, and more are scheduled during the IEEE International Mediterranean Conference on Communications and Networking in Sardinia from 6 to 9 July, and at GLOBECOM in Macau from 7 to 11 December.

As the program continues to grow, it could become a signature ComSoc initiative, one that strengthens the research ecosystem, supports emerging talent, and ensures that promising ideas find pathways to real-world impact.

When Ana Inês Inácio goes to work at the Netherlands Organization for Applied Scientific Research (TNO) in The Hague, she thinks about signals most people never notice: radio waves moving between satellites, sensors, and future wireless networks.

The integrated circuits the research scientist designs lay the foundation for next-generation RF sensor systems critical to advancing radar technologies.

Ana Inês Inácio

EMPLOYER

Netherlands Organization for Applied Scientific Research, TNO

TITLE

Scientist

IEEE MEMBER GRADE

Senior member

ALMA MATER

University of Aveiro, in Portugal

Those invisible RF signals are only part of what earned the IEEE senior member her global recognition.

Inácio recently received the IEEE–Eta Kappa Nu Outstanding Young Professional Award for “leadership in IEEE Young Professionals, fostering innovation and inclusivity, and pioneering advancements in RF sensor systems, bridging technical excellence with impactful community engagement.”

The recognition from IEEE’s honor society reflects a career built along two parallel paths: advancing RF circuit design while helping engineers worldwide build professional communities.

“I’ve always liked building things,” Inácio says. “Sometimes that means circuits; sometimes it means helping people connect and grow together.”

That blend of technical innovation and global leadership gives her work impact far beyond the laboratory.

EE lessons at the kitchen table

Inácio grew up in Vales do Rio, a rural village near Covilhã in central Portugal.

The region was known for farming and textiles, she says. Many residents worked in the textile industry, including her grandfather, who repaired machinery such as industrial looms. He became her first engineering teacher without ever holding the formal title.

Through correspondence courses delivered by mail, he taught himself electrical systems. At home, he explained electricity to his granddaughter while he repaired the household’s appliances and wiring.

“He would show me why something broke and how we could fix it,” she recalls. It sparked her curiosity.

Her mother was a tailor who later managed other tailors. Her father left his factory job to attend culinary school and now cooks at an elder-care facility. Curiosity was a trait that ran through the family.

By high school, Inácio was drawn equally to mathematics and physics and to biology and geology, she says. Encouragement from teachers and an uncle, an engineer, ultimately steered her toward electronics engineering.

Conducting research on integrated circuits

In 2008 she enrolled in an integrated master’s degree program in electrical and telecommunications engineering at the Universidade de Aveiro in Portugal, a five-year degree that combined undergraduate and graduate studies.

An opportunity to study abroad changed her path. In 2012 she moved to the Netherlands to study at Eindhoven University of Technology (TU/e) through a six-month European exchange program with UAveiro.

A professor encouraged her to stay on, so she completed her final year of masters in the Netherlands. She focused on techniques to improve the linearization of RF power amplifiers at Thales. The company, based in Hengelo, Netherlands, designs and produces electronics for defense and security.

She earned her master’s degree from UAveiro in 2013. After graduating, she joined the integrated circuit design group at the University of Twente, in The Netherlands, conducting collaborative research as part of a nationally funded program on linearization techniques for RF front-end systems. The experience introduced her to international research culture and persuaded her to pursue a career abroad, she says.

Engineering the future of wireless

Inácio joined TNO in 2018 as a junior scientist and innovator: her first professional industry job. Today she designs integrated RF front-end systems—the circuits that allow devices to transmit and receive wireless signals.

The components sit at the core of modern communications, enabling sensor networks, satellite links, and emerging 6G technologies.

Her work aims to tackle a central challenge: getting greater performance from smaller chips.

“As communication evolves, we need more bandwidth to transfer more data at higher speeds,” she says. “The question is how much complexity you can integrate into one system while keeping it efficient.”

Unlike commercial lab environments, which reuse established designs, research projects often start from scratch. Each transmit-receive chain—the signal path that converts digital data to radio waves and back again—is tailored to specific requirements.

Her work focuses on improving key circuit characteristics including linearity (ensuring that the signals that go out of the antenna are not distorted) as well as noise reduction (so design blocks can be optimized). Advanced design techniques help devices communicate more reliably while consuming less energy, a critical need for large sensor networks such as the Internet of Things, she says.

Artificial intelligence is beginning to influence her field, she says: “AI is already helping us work faster. The real challenge is learning how to use it to make better designs, not just quicker ones.”

A parallel vocation with IEEE

While her technical career flourished in research labs, an additional journey unfolded through IEEE.

Inácio joined the organization in 2009 as a student after discovering UAveiro’s student branch. What began as curiosity evolved into a long-term leadership path.

She advanced through roles within Region 8—covering Europe, Africa, and the Middle East—one of the organization’s most culturally diverse regions. She was the student branch’s vice chair, and the region’s student representative for more than 22,000 IEEE members. She also served as the Young Professionals Affinity Group chair for the IEEE Benelux Section, which encompasses Belgium, the Netherlands, and Luxembourg.

Currently, she serves as the immediate past chair of the Region 8 Young Professionals Committee, and vice chair and IEEE Member and Geographical Activities representative on the IEEE Young Professionals Committee. In those roles, she represents close to 135,000 IEEE members.

In addition, she is an active member of the IEEE Microwave Theory and Technology Society, currently serving as its Young Professionals liaison.

Her involvement with IEEE has boosted her professional confidence, she says.

“IEEE didn’t directly give me promotions at my day job, but it gave me leadership skills, networking opportunities, and the ability to work with people from everywhere,” she says.

Those experiences now shape her collaborations at TNO, where international teamwork is essential.

The IEEE-HKN Outstanding Young Professional Award recognizes that combination of technical excellence and community impact, she says.

Looking back, Inácio sees a clear thread connecting her childhood curiosity, her international career, and her IEEE leadership: Engineering, she says, is ultimately about people as much as it is about technology.

Cybersecurity consultants have never been more in demand. Information security analyst roles are projected to grow nearly 30 percent between now and 2034, according to the U.S. Bureau of Labor Statistics. More than 15 million cybercrime incidents occurred worldwide in 2024, Statista reported.

Data breaches are costly and pose direct safety risks. Statista reported that more than US $10 trillion is spent annually repairing the damage caused by cybercrime, most commonly phishing, spoofing, extortion, and data breaches. In one example in the United States, breathalyzer devices installed in vehicles became disabled, leaving hundreds of drivers stranded, as detailed in an IEEE Spectrum article.

To help you acquire the skills you need to distinguish yourself from other cybersecurity job candidates, the IEEE Computer Society offers a “What Makes a Great Cybersecurity Consultant” guide. The 23-page PDF includes hard and soft skills you need, a list of certifications to pursue, and key IEEE cybersecurity conferences for staying updated on developments in the field.

The guide includes advice from two cybersecurity experts. John D. Johnson, an IEEE senior member, is the founder and CEO of Aligned Security in Bettendorf, Iowa. Ricardo J. Rodriguez is an associate professor of computer science and systems engineering at the Universidad de Zaragoza, in Spain, who researches digital forensics and other cybersecurity topics.

“Technology, remote work, and a shortage of skilled workers make this the ideal time to consider becoming a cybersecurity consultant,” Johnson says in the guide. “Consulting can give you the flexibility, variety, and control over where you want your career to go.”

Hard and soft skills

At a minimum, cybersecurity professionals should have a general understanding of IT including operating systems, communication protocols, network architecture, and programming languages such as C++, Java, and Python. They also should be well-versed in security auditing, firewall management, penetration testing, and encryption technologies.

The principles of ethical hacking and coding would be handy as well.

“To be able to defend a system well, you first have to know how to attack it,” Rodriguez says.

The guide explains that there are now more technologies available to help cybersecurity consultants monitor threats and protect systems. They include security orchestration, automation, and response (SOAR) platforms, which automate workflows to collect security data, streamline incident response, and automate repetitive tasks.

Rodriguez points to advances in domain name system security extensions (DNSSEC), which uses digital signatures based on public-key cryptography to strengthen the authentication of the domain name system. By validating data authenticity, DNSSEC safeguards against attacks such as DNS spoofing and guarantees that users connect to the correct IP address.

Technologies such as artificial intelligence, blockchain, and quantum computing will increasingly be used to help thwart cyberattacks, the guide suggests. AI is expected to enhance the quality of data analysis, Rodriguez says.

Although hard skills are important, soft skills are just as crucial, according to the guide. Critical thinking, project management, flexibility, teamwork, and organizational and presentation skills are essential.

It’s not enough to be good at analyzing security vulnerabilities; you also need to clearly describe the situation and explain possible solutions.

“Soft skills are important to achieve good team cohesion,” Rodriguez says, “because consultants often lead diverse teams from within their client’s organization.”

“It’s essential,” Johnson adds, “that you demonstrate to clients you’re a team player and a capable communicator, and that you meet your commitments.”

Security certifications

Possessing security-specific credentials is a valuable way to demonstrate your expertise to potential clients, according to the guide. Because hundreds of certifications are available, Johnson says, pinpointing the most relevant ones can be challenging. Some people focus on theoretical knowledge, while others want to cover practical applications of technology.

“Survey the industry and compare it to your skills,” Johnson recommends. “Decide what you want to do, and identify where you have gaps in your skills and experience.”

Here are four of the nine certifications listed in the guide that are frequently cited as being important. All the providers are cybersecurity organizations.

• Certified information security manager. This globally recognized certification from the ISACA is for professionals managing enterprise information security.
• Certified cloud security professional. Offered by ISC2, this credential validates advanced technical skills in designing, managing, and securing cloud infrastructure.
• Certified ethical hacker. This certification from the International Council of E-Commerce Consultants (C-Council) confirms proficiency in using methods commonly employed by malicious hackers to detect vulnerabilities.
• Offensive security certified professional. A hands-on, 24-hour certification exam offered by OffSec covers practical testing skills.

Additional industry-specific certifications might be required for organizations in finance, government, health care, or manufacturing.

Sound general knowledge—backed by experience, training, and certification—is an essential foundation for being a specialist, Johnson says.

Conferences and networking opportunities

Events sponsored by the IEEE Computer Society can help you learn about the latest research and advancements in cybersecurity:

• IEEE Symposium on Security and Privacy, from 18 to 21 May in San Francisco.
  
• IEEE European Symposium on Security and Privacy, from 6 to 10 July in Lisbon.
  
• IEEE International Conference on Cyber Security and Resilience, from 3 to 5 August in Lisbon.
  
• IEEE Secure Development Conference, from 14 to 16 October in Indianapolis.

Conferences can give you insight into the field and let you do some networking, but it’s important to network elsewhere as well, experts say. Consider joining the IEEE Technical Community on Security and Privacy, which connects experts and professionals advancing research in areas such as encryption, operating system security, and data privacy.

Learning and meeting people keeps your knowledge sharp and can lead to mentorship opportunities with established cybersecurity consultants, Johnson says.

Other IEEE resources

The IEEE Computer Society’s cybersecurity resources page offers a wealth of information including fundamentals, possible career paths, and standards development. To keep you updated on trends, the society publishes IEEE Transactions on Privacy and the IEEE Security and Privacy magazine.

In addition to the guide, the IEEE Learning Network offers nearly 30 courses on cybersecurity. And you can find research papers in the IEEE Xplore Digital Library.

When Yong Wang recently received one of the highest honors for early-career data visualization researchers, it marked a milestone in an extraordinary journey that began far from the world’s technology hubs.

Wang was born in a small farming village in southern China to parents with limited formal education. Today the IEEE member and associate editor of IEEE Transactions on Visualization and Computer Graphics is an assistant professor in the College of Computing and Data Science atNanyang Technological University, in Singapore. He studies how people can employdata visualization techniques to get more out of large-scale datasets as well as advanced artificial intelligence techniques.

“Visualization helps people understand complex ideas,” he says. “If we design these tools well, they can make advanced technologies accessible to everyone.”

For his work in the field, theIEEE Computer Society visualization and graphics technical committee presented him with its 2025 Significant New Researcher Award. The recognition highlights his growing influence in fields including data visualization, human-computer interaction and human-AI collaboration—areas becoming more important as the world generates more data than humans can easily interpret.

YONG WANG

EMPLOYER

Nanyang Technological University, in Singapore

POSITION

Assistant professor of computing and data science

IEEE MEMBER GRADE

Member

ALMA MATERS

Harbin Institute of Technology in China; Huazhong University of Science and Technology in Wuhan, China; Hong Kong University of Science and Technology

“Visualization helps people understand complex ideas,” Wang says. “If we design these tools well, they can make advanced technologies accessible to everyone.”

Growing up in rural Hunan

Wang was born in in a small farming village in southern China. China’s economy was still developing, and life in his village was modest. Most families in Hunan grew rice, vegetables, and fruit to support themselves.

Wang’s parents worked in agriculture too, and his father often traveled to cities to earn money working in a factory or on construction jobs. The extra income helped support the family and made it possible for Wang to attend college.

“I’m very grateful to my parents,” Wang says. “They never attended university, but they strongly supported my education.”

“If we build tools that help people understand information, then more people can participate in science and innovation. That’s the real power of visualization.”

Technology was scarce in the village, he says. Computers were almost nonexistent, and televisions were considered precious, expensive household possessions.

One childhood memory still makes him laugh: During a summer vacation, he and his brother spent so many hours playing video games on a simple console connected to the family’s television that the TV screen eventually burned out.

“My mother was very angry,” he recalls. “At that time, a TV was a very valuable thing.”

He says that despite never having used a laptop or experimenting with electronic equipment, he was fascinated by the technologies he saw on TV shows.

Discovering robotics and engineering

His parents encouraged a practical career such as medicine or civil engineering, but he felt drawn to robotics and computing, he says.

“I didn’t really understand what computer science involved,” he says. “But from what I saw on TV, it looked exciting and advanced.”

He enrolled at Harbin Institute of Technology, in northeastern China. The esteemed university is known for its engineering programs. His major—automation—combined elements of electrical engineering, robotics, and control systems.

One of the defining experiences of his undergraduate years, he says, was a university robotics competition. Wang and his teammates designed a robot capable of autonomously navigating around obstacles.

The design was simple compared with professional systems, he acknowledges. But, he says, the experience was exhilarating. His team placed second, and Wang began to see engineering as both creative and collaborative.

He graduated with a bachelor’s degree in 2011, and then pursued a master’s degree in pattern recognition and image processing from the Huazhong University of Science and Technology, in Wuhan, China.

In 2014 he took a position as a research intern working at a technology company in Shenzhen, China.

That experience helped him clarify his future, he says: “I realized I didn’t enjoy doing repetitive work or simply following instructions. I wanted to explore ideas that interested me, and I wanted to conduct research.” The realization pushed him toward graduate school, he says.

In 2014 he took a position as a research intern working a technology company in Shenzhen, China. That experience helped him clarify his future, he says: “I realized I didn’t enjoy doing repetitive work or simply following instructions. I wanted to explore ideas that interested me, and I wanted to conduct research.” The realization pushed him toward graduate school, he says.

Building tools that help humans work with AI

He enrolled in the computer science Ph.D. program at the Hong Kong University of Science and Technology and earned the degree in 2018. He remained there as a postdoctoral researcher until 2020, when he moved to Singapore to join Singapore Management University as an assistant professor of computing and information systems. He moved over to Nanyang Technological University as an assistant professor in 2024.

His research focuses on a challenge facing nearly every business: how to make sense of the enormous amounts of data being generated.

He and his students, collaborators have developed a series of approaches to recommend or automatically generate appropriate visualizations, including infographics.

It allows nontechnical people to create visualizations instead of hiring professional designers.

Another focus of Wang’s research is human-AI collaboration. AI systems can analyze data at enormous scale, but people still need to be the final decision-makers, he says.

Visualization helps bridge the gap between human intention and AI’s complex calculations by making the process an AI system uses to reach a result more transparent and understandable.

“If people understand how the AI system works,” Wang says, “they can collaborate with it more effectively.”

He recently explored how visualization techniques could help researchers understand quantum computing, a field where core concepts—such as superposition, where a bit can be in more than one state at a time—are abstract. In classical computing, the bit state is binary: It’s either 1 or 0. A quantum bit, or qubit, can be 1, 0, or both. The differences get more dizzying from there.

Visualization tools could help scientists monitor quantum systems and interpret quantum machine-learning models, he says.

The importance of IEEE communities

“We live in an era of information explosions,” Wang says. “Huge amounts of data are generated, and it’s difficult for people to interpret all of it to make better business decisions.”

Data visualization offers a solution by turning complex information into images, patterns, and diagrams that people can more readily understand.

But many visualizations still must be designed manually by experts, Wang notes. It’s a time-consuming process that creates a bottleneck, he says.

His solution is to use large language models and multimodal systems that can generate text, images, video, and sensor data simultaneously and automate parts of the process.

One system developed by his research group lets users design complex infographics through natural-language instructions combined with simple interactions such as drawing on a touchscreen with a finger. It allows nontechnical people to generate visualizations instead of hiring professional designers.

Another focus of his research is human-AI collaboration. AI systems can analyze data at enormous scale, but people still need to be the final decision-makers, he says.

Visualization helps bridge the gap between human intention and AI’s complex calculations by making the process an AI system uses to reach a result more transparent and understandable.

“If people understand how the AI system works,” he says, “they can collaborate with it more effectively.”

He recently explored how visualization techniques could help researchers understand quantum computing, a field where core concepts—such as superposition, where a bit can be in more than one state at a time—are abstract. In classical computing, the bit state is binary: It’s either 1 or 0. A quantum bit, or qubit, can be 1, 0, or both. The differences get more dizzying from there.

Visualization tools could help scientists monitor quantum systems and interpret quantum machine-learning models, he says.

The importance of IEEE communities

Teaching and mentoring students remain among the most meaningful parts of Wang’s career, he says.

Professional communities such as the IEEE Computer Society, he says, play a major role in helping him transform early-stage graduate students unsure of which lines of inquiry they will pursue into independent researchers with a solid technical focus. Through conferences, publications, and technical committees, IEEE connects Wang with other researchers working in visualization, AI, and human-computer interactions, he says.

Those connections have helped him share ideas, collaborate, and stay up to date on innovations in the research community.

Receiving the Significant New Researcher award motivates him to continue pushing the field forward, he says.

Looking back, he says, the distance between his rural village in Hunan and an international research career still feels remarkable. But, he says, the journey reflects something larger about his chosen field: “If we build tools that help people understand information, then more people can participate in science and innovation.

“That’s the real power of visualization.”

Tom Burick has always considered himself a builder. Over the years he’s designed robots, constructed a vintage teardrop trailer, and most recently, led a group of students in building a full-scale replica of a pivotal 1940s computer.

Burick is a technology instructor at PS Academy in Gilbert, Ariz., a middle and high school for students with autism and other specialized learning needs. At the start of the 2025–26 school year, he began a project with his students to build a full-scale replica of the Electronic Numerical Integrator and Computer, or ENIAC, for the 80th anniversary of the historic computer’s construction. ENIAC was one of the world’s first programmable electronic computers. When it was built, it was about one thousand times as fast as other machines.

Before becoming a teacher, Burick owned a robotics company for a decade in the 2000s. But when a financial downturn forced him to close the business, he turned to teaching. “I had so many amazing people help me when I was young [who] really gave me their time and resources, and really changed the trajectory of my life,” Burick says. “I thought I need to pay that forward.”

Becoming a Roboticist

As a young child in Latrobe, Pa., Burick watched the television show Lost in Space, which includes a robot character who protects the family. “He was the young boy’s best friend, and I was so captivated by that. I remember thinking to myself, I want that in my life. And that started that lifelong love affair with robotics and technology.”

He started building toy robots out of anything he could find, and in junior high school, he began adding electronics. “By early high school, I was building full-fledged autonomous, microprocessor-controlled machines,” he says. At age 15, he built a 150-pound steel firefighting robot, for which he won awards from IEEE and other organizations.

Burick kept building robots and reached out for help from local colleges and universities. He first got in touch with a student at Carnegie Mellon University, who invited him to visit campus. “My parents drove me down the next weekend, and he gave me a tour of the robotics lab. I was mesmerized. He sent me home with college textbooks and piles of metal and gears and wires,” Burick says. He would read the textbook a page at a time, reading it again and again until he felt he had an understanding of it. Then, to help fill gaps in his understanding, he got in touch with a robotics instructor at Saint Vincent College, in his hometown of Latrobe, who let him sit in on classes. Each of these adults, he says, “helped change the trajectory of my life.”

Toward the end of high school, Burick realized that college wouldn’t be the right environment for him. “I was drawn to real-world problem-solving rather than structured coursework and I chose to continue along that path,” he says. Additionally, Burick has dyscalculia, which makes traditional mathematics more challenging for him. “It pushed me to develop alternative methods of engineering.”

The ENIAC replica Burick’s students built precisely matches what the original computer would have looked like before it was disassembled in the 1950s. Robert Gamboa

When he graduated, he worked in several tech jobs before starting his own company. In 2000, he opened a computer retail store and adjacent robotics business, White Box Robotics. The idea for the company came when Burick was building a “white box” PC from standard, off-the-shelf components, and realized there was no comparable product for robotics.

So, he started developing a modular, general-purpose platform that applied white box PC standards to mobile robots. “The robot’s chassis was like a box of Legos,” he says. You could click together two torsos to double its payload, switch out the drive system, or swap its head for a different set of sensors. He filed utility and design patents for the platform, called the 914 PC-Bot, and after merging with a Canadian defense robotics company called Frontline Robotics, started production. They sold about 200 robots in 17 countries, Burick says.

Then the 2008 financial crisis hit. White Box Robotics held on for a couple of years, shuttering in late 2010. “I got to live my life’s dream for 10 years,” he says. After closing White Box, “there was some soul searching” about what to do next. He recalled the impact his own mentors had, and decided to pay it forward by teaching.

Neurodiversity as a Superpower

In 2013, Burick started working in a vocational training program for young adults living with autism. The program didn’t have a technical arm, so he started one and ran it until 2019, when he was hired to be a technology instructor at PS Academy Arizona.

Burick and one of his students assemble the base for one of ENIAC’s three portable function tables, which contained banks of switches that stored numerical constants. Bri Mason

Burick feels he can connect with his students, because he is also neurodivergent. Throughout his childhood, he was told what he wasn’t able to do because of his dyscalculia diagnosis. “People tell you what it takes, but they never tell you what it gives,” Burick says.

In adulthood, he realized that some of his strengths are linked to dyscalculia, too, like strong 3D spatial reasoning. “I have this CAD program that runs in my head 24 hours a day,” he says. “I think the reason I was successful in robotics, truly, was because of the dyscalculia…. To me, [it] has always been a superpower.”

Whenever his students say something disparaging about living with autism, he shares his own experience. “You need to have maybe just a bit more tenacity than others, because there are parts of it you do have to fight through, but you come through with gifts and strengths,” he tells them.

And Burick’s classes aim to play to those strengths. “I didn’t want my technology program to feel like craft hour,” he says. Instead, through projects like the ENIAC replica, students can leverage traits many of them share, like the abilities to hyperfocus and to precisely repeat tasks.

Recreating ENIAC

Burick has taught his students about ENIAC for several years. While reading about it, he learned that the massive, 27-tonne computer was dismantled and partially destroyed after being decommissioned in 1955. Although a few of ENIAC’s 40 original panels are on display at museums, “there was no hope of ever seeing it together again. We wanted to give the world that experience,” Burick says.

He and his students started by learning about ENIAC, and even Burick was surprised by how complex the 80-year-old computer was. They built a one-twelfth scale model to help the students better understand what it looked like. Seeing the students light up, Burick became confident in their ability to move onto the full-scale model, and he started ordering supplies.

ENIAC was composed of 40 large metal panels arranged in a U-shape that housed its many vacuum tubes, resistors, capacitors, and switches. Twenty of the panels were accumulators with the same design, so the students started with these, then worked through smaller groupings of panels. The repeating panels brought symmetry to ENIAC, Burick says, but it was also one of the main challenges of recreating it. If one part was slightly out of place, the next one would be too and the mistake would compound.

The students installed 500 simulated vacuum tubes in each of the panels here, for a total of 18,000 vacuum tubes.Robert Gamboa

Once they constructed the panels, they added ENIAC’s three function tables, which stored numerical constants in banks of switches, then two punch-card machines. Finally, they installed 18,000 simulated vacuum tubes. In total, the project used nearly 300 square meters of thick-ream cardboard, 1,600 hot-glue-gun sticks, and 7 gallons of black paint.

The scale of the machine—and his students’ work—left Burick in awe. “By the time we were done, I felt like I was in a room full of scientists,” he says.

Previously, Burick’s students built an 8-foot-long drivable Tesla Cybertruck (“complete with a 400-watt stereo system and a subwoofer”) and he plans to keep the momentum with another recreation—maybe from the Apollo moon missions.

“I go to work every day, and I feel passionate about robotics [and] technology. I get to share that passion with the students,” Burick says. “I get to feel what it’s like to be in the position of the people that helped me. It closes that loop, and I find that really rewarding.”

This article is crossposted from IEEE Spectrum’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free!

The Individual Contributor–Manager Fork: It’s Not a Promotion. It’s a Profession Change.

When I was promoted to engineering manager of a mid-sized team at Clorox, I thought I had made it.

More money. More stock. More visibility. More proximity to senior leadership. From the outside, and on paper, it was clearly a promotion.

I had often heard the phrase, “Management isn’t a promotion. It’s a job switch.” I brushed it off as cliché advice engineers tell each other to sound wise.

It turns out both things were true. It was a promotion. It was also an entirely different job.

And I was nowhere near ready for what that meant.

A Shift in Priorities

There’s surprisingly little training for new managers. As engineers, we’re highly technical and used to mastering complex systems. Many of us assume managing people will be easier than distributed systems. Or we assume it’s just “more meetings.”

Both assumptions are wrong.

Yes, I had more meetings. But what changed most wasn’t my calendar, it was how my impact was measured. As an individual contributor, my output was visible. Code shipped. Features delivered. Bugs fixed.

As a manager, my impact became indirect. It flowed through other people.

That shift was disorienting.

So I fell back into my comfort zone. I started writing more code. I tried to be the strongest engineer on the team. It felt productive and measurable.

It was also a mistake.

By trying to be the number one engineer, I was neglecting my actual job. I wasn’t supporting senior engineers. I wasn’t unblocking systemic problems. I wasn’t building career paths. I was competing with the very people I was supposed to enable.

Management is about amplification.

Learning to Redefine Impact

The turning point came when I began each week with a simple question:

What is the single most impactful thing I can do right now?

Often, it wasn’t code. It was writing a document that clarified direction. It was fixing a broken process with a single point of failure. It was redistributing ownership so that knowledge wasn’t concentrated in one person.

I started deliberately removing myself from implementation work. I committed to writing almost no code. That forced trust. It also revealed gaps in the system that I could address at the right level: through coaching, documentation, hiring, or process changes.

Another major shift was taking one-on-one meetings seriously.

Many engineers dislike one-on-ones. They can feel awkward or devolve into status updates. I scheduled them every other week and approached them with a mix of tactical alignment and human check-in.

I rarely started with engineering questions. Instead:

• Are you happy with the work you’re doing?
  
• Do you feel stretched or stagnant?
  
• What’s frustrating you right now?

Burnout doesn’t show up in Jira tickets. Neither does quiet disengagement.

Those conversations helped me anticipate turnover, redistribute workload, and build trust.

I also spent more time thinking about career ladders. Was I giving my team the kind of work that would help them grow? Was I hoarding high-visibility projects? Was I clear about what senior-level impact looked like?

That work felt less tangible than code, but it moved the needle far more.

Why I Went Back to IC

Ultimately, I returned to the individual contributor track.

Part of it was practical: I was laid off from my management role, and the market rewarded senior IC roles more strongly at the time. But if I’m honest, the deeper reason was simpler.

I love writing code.

I enjoy improving systems and helping people, but the part of my day that energized me most was still building. Management required relinquishing that. You can’t be absorbed in technical implementation and deeply people-focused at the same time. Something has to give.

Personally, I don’t need to climb the corporate ladder to feel successful. And you might not have to. Many organizations offer technical leadership tracks that are truly in parity with management when it comes to salary bands. Staff and principal engineers steer strategy without managing people.

If you want to remain deeply technical, you should think very carefully before moving into people management. It requires surrendering control over implementation and focusing on alignment, growth, and long-range planning. If you don’t genuinely care about those things, you won’t just be unhappy, you’ll make your team unhappy.

A Simple Test Before You Choose

Before taking a management role, ask yourself:

• Do I get energy from solving people-problems every day?
  
• Am I comfortable measuring impact indirectly?
  
• Would I be satisfied if I rarely wrote production code again?
  
• Do I want leverage or craft?

There’s no right answer.

The IC/manager fork isn’t about prestige. It’s about what kind of work you want your days to consist of.

Choose based on energy, not ego.

—Brian

12 Graphs That Explain the State of AI in 2026

Stanford University’s AI Index is out for 2026, tracking trends and noble developments in artificial intelligence. This year, China has taken a notable lead in AI model releases and industrial robotics compared to previous years. AIs are rapidly reaching benchmarks and achieving high levels of compute, but public trust in AI and confidence in government regulation of AI is mixed.

Read more here.

AI Models Trained on Physics Are Changing Engineering

Much like large language models have learned from existing texts, new AI physics models are being trained on simulation results. This results in “large physics models” that can simulate situations in transportation, aerospace, or semiconductor engineering much faster than traditional physics simulations. Using new AI physics models “can be anywhere between 10,000 to close to a million times faster,” says Jacomo Corbo, CEO and co-founder of PhysicsX.

Read more here.

Temple University Student Highlights IEEE Membership Perks

Kyle McGinley is an IEEE Student Member pursuing a bachelor’s degree in electrical and computer engineering at Temple University. Joining IEEE helped him to develop the skills necessary for real-world teams. “In school, they don’t teach you how to communicate with people. They only teach you how to remember stuff,” he says.

Read more here.

When the robotics engineering field that Maja Matarić wanted to work in didn’t exist, she helped create it. In 2005 she helped define the new area of socially assistive robotics.

As an associate professor of computer science, neuroscience, and pediatrics at the University of Southern California, in Los Angeles, she developed robots to provide personalized therapy and care through social interactions.

Maja Matarić

Employer

University of Southern California, Los Angeles

Job Title

Professor of computer science, neuroscience, and pediatrics

Member grade

Fellow

Alma maters

University of Kansas and MIT

The robots could have conversations, play games, and respond to emotions.

Today the IEEE Fellow is a professor at USC. She studies how robots can help students with anxiety and depression undergo cognitive behavioral therapy. CBT focuses on changing a person’s negative thought patterns, behaviors, and emotional responses.

For her work, she received a 2025 Robotics Medal from MassRobotics, which recognizes female researchers advancing robotics. The Boston-based nonprofit provides robotics startups with a workspace, prototyping facilities, mentorship, and networking opportunities.

When receiving the award at the ceremony in Boston, Matarić was overcome with joy, she says.

“I’ve been very fortunate to be honored with several awards, which I am grateful for. But there was something very special about getting the MassRobotics medal, because I knew at least half the people in the room,” she says. “Everyone was just smiling, and there was a great sense of love.”

Seeing herself as an engineer

Matarić grew up in Belgrade, Serbia. Her father was an engineer, and her mother was a writer. After her father died when she was 16, Matarić and her mother moved to the United States.

She credits her father for igniting her interest in engineering, and her uncle who worked as an aerospace engineer for introducing her to computer science.

Matarić says she didn’t consider herself an engineer until she joined USC’s faculty, since she always had worked in computer science.

“In retrospect, I’ve always been an engineer,” Matarić says. “But I didn’t set out specifically thinking of myself as one—which is just one of the many things I like to convey to young people: You don’t always have to know exactly everything in advance.”

Maja Matarić and her lab are exploring how socially assistive robots can help improve the communication skills of children with autism spectrum disorder. National Science Foundation News

While pursuing her bachelor’s degree in computer science at the University of Kansas in Lawrence, she was introduced to industrial robotics through a textbook. After earning her degree in 1987, she had an opportunity to continue her education as a graduate student at MIT’s AI Lab (now the Computer Science and Artificial Intelligence Lab). During her first year, she explored the different research projects being conducted by faculty members, she said in a 2010 oral history conducted by the IEEE History Center. She met IEEE Life Fellow Rodney Brooks, who was working on novel reactive and behavior-based robotic systems. His work so excited her that she joined his lab and conducted her master’s thesis under his tutelage.

Inspired by the way animals use landmarks to navigate, Matarić developed Toto, the first navigating behavior-based robot. Toto used distributed models to map the AI Lab building where Matarić worked and plan its path to different rooms. Toto used sonar to detect walls, doors, and furniture, according to Matarić’s paper, “The Robotics Primer.”

After earning her master’s degree in AI and robotics in 1990, she continued to work under Brooks as a doctoral student, pioneering distributed algorithms that allowed a team of up to 20 robots to execute complex tasks in tandem, including searching for objects and exploring their environment.

Matarić earned her Ph.D. in AI and robotics in 1994 and joined Brandeis University, in Waltham, Mass., as an assistant professor of computer science. There she founded the Interaction Lab, where she developed autonomous robots that work together to accomplish tasks.

Three years later, she relocated to California and joined USC’s Viterbi School of Engineering as an assistant professor in computer science and neuroscience.

In 2002 she helped to found the Center for Robotics and Embedded Systems (now the Robotics and Autonomous Systems Center). The RASC focuses on research into human-centric and scalable robotic systems and promotes interdisciplinary partnerships across USC.

Matarić’s shift in her research came after she gave birth to her first child in 1998. When her daughter was a bit older and asked Matarić why she worked with robots, she wanted to be able to “say something better than ‘I publish a lot of research papers,’ or ‘it’s well-recognized,’” she says.

“In academia, you can be in a leadership role and still do research. It’s a wonderful and important opportunity that lets academics be on top of our field and also train the next generation of students and help the next generation of faculty colleagues.”

“Kids don’t consider those good answers, and they’re probably right,” she says. “This made me realize I was in a position to do something different. And I really wanted the answer to my daughter’s future question to be, ‘Mommy’s robots help people.’”

Matarić and her doctoral student David Feil-Seifer presented a paper defining socially assistive robotics at the 2005 International Conference on Rehabilitation Robotics. It was the only paper that talked about helping people complete tasks and learn skills by speaking with them rather than by performing physical jobs, she says.

Feil-Seifer is now a professor of computer science and engineering at the University of Nevada in Reno.

At the same time, she founded the Interaction Lab at USC and made its focus creating robots that provide social, rather than physical, support.

“At this point in my career journey, I’ve matured to a place where I don’t want to do just curiosity-driven research alone,” she says. “Plenty of what my team and I do today is still driven by curiosity, but it is answering the question: ‘How can we help someone live a better life?’”

In 2006 she was promoted to full professor and made the senior associate dean for research in USC’s Viterbi School of Engineering. In 2012 she became vice dean for research.

“In academia, you can be in a leadership role and still do research,” she says. “It’s a wonderful and important opportunity that lets academics be on top of our field and also train the next generation of students and help the next generation of faculty colleagues.”

Research in socially assistive robotics

One of the longest research projects Matarić has led at her Interaction Lab is exploring how socially assistive robots can help improve the communication skills of children with autism spectrum disorder. ASD is a lifelong neurological condition that affects the way people interact with others, and the way they learn. Children with ASD often struggle with social behaviors such as reading nonverbal cues, playing with others, and making eye contact.

Matarić and her team developed a robot, Bandit, that can play games with a child and give the youngster words of affirmation. Bandit is 56 centimeters tall and has a humanlike head, torso, and arms. Its head can pan and tilt. The robot uses two FireWire cameras as its eyes, and it has a movable mouth and eyebrows, allowing it to exhibit a variety of facial expressions, according to the IEEE Spectrum’s robots guide. Its torso is attached to a wheeled base.

The study showed that when interacting with Bandit, children with ASD exhibited social behaviors that were out of the ordinary for them, such as initiating play and imitating the robot.

Matarić and her team also studied how the robot could serve as a social and cognitive aid for elderly people and stroke patients. Bandit was programmed to instruct and motivate users to perform daily movement exercises such as seated aerobics.

Maja Matarić and doctoral student Amy O’Connell testing Blossom, which is being used to study how it can aid students with anxiety or depression.University of Southern California

Over the years, Matarić’s lab developed other robots including Kiwi and Blossom. Kiwi, which looked like an owl, helped children with ASD learn social and cognitive skills, helped motivate elderly people living alone to be more physically active, and mediated discussions among family members. Blossom, originally developed at Cornell, was adapted by the Interaction Lab to make it less expensive and personalizable for individuals. The robot is being used to study how it can aid students with anxiety or depression to practice cognitive behavioral therapy.

Matarić’s line of research began when she learned that large language model (LLM) chatbots were being promoted to help people with mental health struggles, she said in an episode of the AMA Medical News podcast.

“It is generally not easy to get [an appointment with a] therapist, or there might not be insurance coverage,” she said. “These, combined with the rates of anxiety and depression, created a real need.”

That made the chatbot idea appealing, she says, but she was interested to see if they were effective compared with a friendly robot such as Blossom.

Matarić and her team used the same LLMs to power CBT practice with a chatbot and with Blossom. They ran a two-week study in the USC dorms, where students were randomly assigned to complete CBT exercises daily with either a chatbot or the robot. Participants filled out a clinical assessment to measure their psychiatric distress before and after each session.

The study showed that students who interacted with the robot experienced a significant decrease in their mental state, Matarić said in the podcast, and students who interacted with the chatbot did not.

“Joining an [IEEE] society has an impact, and it can be personal. That’s why I recommend my students join the organization—because it’s important to get out there and get connected.”

She and her team also reviewed transcripts of conversations between the students and the robot to evaluate how well the LLM responded to the participants. They found the robot was more effective than the chatbot, even though both were using the same model.

Based on those findings, in 2024 Matarić received a grant from the U.S. National Institute of Mental Health to conduct a six-week clinical trial to explore how effective a socially assistive robot could be at delivering CBT practice. The trial, currently underway, also is expected to study how Blossom can be personalized to adapt to each user’s preferences and progress, including the way the robot moves, which exercises it recommends, and what feedback it gives.

During the trial, the 120 students participating are wearing Fitbits to study their physiologic responses. The participants fill out a clinical assessment to measure their psychiatric distress before and after each session.

Data including the participants’ feelings of relating to the robot, intrinsic motivation, engagement, and adherence will be assessed by the research team, Matarić says.

She says she’s proud of the graduate students working on this project, and seeing them grow as engineers is one of the most rewarding parts of working in academia.

“Engineers generally don’t anticipate having to work with human study participants and needing to understand psychology in addition to the hardcore engineering,” she says. “So the students who choose to do this research are just wonderful, caring people.”

Finding a community at IEEE

Matarić joined IEEE as a graduate student in 1992, the year she published her first paper in IEEE Transactions on Robotics and Automation. The paper, “Integration of Representation Into Goal-Driven Behavior-Based Robots,” described her work on Toto.

As a member of the IEEE Robotics and Automation Society, she says she has gained a community of like-minded people. She enjoys attending conferences including the IEEE International Conference on Robotics and Automation, the IEEE/RSJ International Conference on Intelligent Robots and Systems, and the ACM/IEEE International Conference on Human-Robot Interaction, which is closest to her field of research.

Matarić credits IEEE Life Fellow George Bekey, the founding editor in chief of the IEEE Transactions on Robotics, for recruiting her for the USC engineering faculty position. He knew of her work through her graduate advisor Brooks, who published a paper in the journal that introduced reactive control and the subsumption architecture, which became the foundation of a new way to control robots. It is his most cited paper. Bekey, who was editor in chief at the time, helped guide Brooks through the challenging review process. Matarić joined Brooks’s lab at MIT two years after its publication, and her work on Toto built on that foundation.

“Joining a society has an impact, and it can be personal,” she says. “That’s why I recommend my students join the organization—because it’s important to get out there and get connected.”

Roughly 90 percent of hard tech startups fail due to funding constraints, longer R&D timelines for developing hardware, and the complexity of manufacturing their products, according to a number of studies.

Generally, these startups require up to 50 percent more investor financing than software ones, according to a Medium article. Typically, they need at least US $30 million, according to a Lucid article. That’s double the funding needed by software companies on average.

To help them connect with investors, IEEE Entrepreneurship in 2024 launched its Hard Tech Venture Summits. The two-day events connect founders with potential investors and other entrepreneurs. Attendees include manufacturers, design engineers, and intellectual property lawyers.

“Even though there are a lot of startup investor conferences, it’s hard to find those focused on hard tech,” says Joanne Wong, who helped initiate the program and is now the chair. She is a general partner at Redds Capital, a California-based venture capital firm that invests in global early-stage IT startups.

The IEEE member is also an entrepreneur. She founded SciosHub in 2020. The company’s software-as-a-service and informatics platform automates the data-management process for biomedical research labs.

“Many investors are focused on AI software—which is good,” she says. “But for hard tech companies, it is still hard to find support.”

The summit also includes a workshop to help founders navigate manufacturing processes and regulatory compliance. The event is open to IEEE members and others.

IEEE is a natural fit for the program, Wong says, because hard tech is synonymous with electrical engineering.

“Some of the domains we’re covering are robotics, semiconductors, and aerospace technology. IEEE has societies for all these fields,” she says. “Because of that, there are many resources within the organizations for startups, whether it be mentors or guides on how to commercialize products.”

There are several venture summits planned for this year. Two are scheduled in collaboration with the IEEE Systems Council: this month in Menlo Park, Calif., and in October in Toronto.

On 10 and 11 June, a third summit is scheduled to take place in Boston at the IEEE Microwave Theory and Technology Society’s International Microwave Symposium.

More events are being planned for next year in Asia, Europe, Latin America, and North America.

Networking and a pitch competition

Each summit includes keynote speakers, followed by networking roundtables. Each table is composed of people from three to five startups, one or two investors, and a service provider.

That arrangement helps founders build relationships, which is the summit organizers’ priority, Wong says. Investors at past events have included i3 Ventures, Monozukuri Ventures, and TSV Capital.

“The connection with the community was fantastic, especially investors and founders in robotics.” —Mark Boysen, founder of Naware

Startups present their pitch, which a number of investors evaluate before ranking the business plan and product. The top 10 startups pitch their business to all the investors.

On the second day, the startup founders participate in a half-day engineering design–to–manufacturing workshop, at which manufacturing engineers teach them how to navigate the process and meet regulations.

In an exhibition area, participants can see demonstrations from the startups and connect with service providers.

The 2025 event’s half-day engineering design–to–manufacturing workshop was led by Liz Taylor, president of DOER Marine. The company manufactures marine equipment.Larissa Abi Nakhle/IEEE

Positive feedback from attendees

In a survey of past summit attendees, startup founders said the event connected them not only with investors but also with other entrepreneurs having similar struggles.

“The connection with the community was fantastic, especially investors and founders in robotics,” said Mark Boysen, who founded Naware. The company, based in Edina, Minn., developed a robot that uses AI to detect and remove weeds from golf courses, parks, and lawns.

“I loved getting the investors’ perspectives and understanding what they’re looking for,” Boysen said.

Jeffrey Cook, who attended a summit in 2024, said he met “a lot of great contacts and saw what the hard tech venture climate is like.”

Attendees of the Hard Tech Venture Summit spend the first day networking and presenting their pitch to investors. IEEE Entrepreneurship

“Those in the community would benefit from coming to the summit,” said Cook, who founded Gigantor Technologies in Melbourne Beach, Fla. It develops hardware systems for AI-powered devices.

More than 90 percent of attendees at the 2025 event in San Francisco said they would highly recommend the summit to others, according to a survey.

Investors and service providers also have found the events successful.

Ji Ke, a partner and the chief technology officer of deep tech VC firm SOSV, attended the 2025 summit.

“I met a lot of young entrepreneurs tackling some big challenges,” he said. “This is one of the best events to meet some very-early-stage companies.”

Making important connections in hard tech

Startup founders who want to attend a summit must apply. Applications for this year’s events are open. Participants must be founders of preseed, seed, or Series A startups.

Preseed founders are seeking small investments to get their businesses off the ground. Those in the seed stage have already secured funding from their first investor. Series A startups have obtained funding and are developing their product.

Applicants are reviewed by a committee of investors to ensure the startups would be a good fit. Those who are approved are matched with investors and service providers based on their specialty.

“The journey for a hard tech startup is very long and arduous,” Wong says. “Founders need to meet as many investors as possible and other people who support hard tech systems so that they’re able to reach out to them for advice or help.”

Those interested in learning more about an upcoming event can send a request to entrepreneurship@ieee.org.

Like many engineers, Sarang Gupta spent his childhood tinkering with everyday items around the house. From a young age he gravitated to projects that could make a difference in someone’s everyday life.

When the family’s microwave plug broke, Gupta and his father figured out how to fix it. When a drawer handle started jiggling annoyingly, the youngster made sure it didn’t do so for long.

Sarang Gupta

Employer

OpenAI in San Francisco

Job

Data science staff member

Member grade

Senior member

Alma maters

The Hong Kong University of Science and Technology; Columbia

By age 11, his interest expanded from nuts and bolts to software. He learned programming languages such as Basic and Logo and designed simple programs including one that helped a local restaurant automate online ordering and billing.

Gupta, an IEEE senior member, brings his mix of curiosity, hands-on problem-solving, and a desire to make things work better to his role as member of the data science staff at OpenAI in San Francisco. He works with the go-to-market (GTM) team to help businesses adopt ChatGPT and other products. He builds data-driven models and systems that support the sales and marketing divisions.

Gupta says he tries to ensure his work has an impact. When making decisions about his career, he says, he thinks about what AI solutions he can unlock to improve people’s lives.

“If I were to sum up my overall goal in one sentence,” he says, “it’s that I want AI’s benefits to reach as many people as possible.”

Pursuing engineering through a business lens

Gupta’s early interest in tinkering and programming led him to choose physics, chemistry, and math as his higher-level subjects at Chinmaya International Residential School, in Tamil Nadu, India. As part of the high school’s International Baccalaureate chapter, students select three subjects in which to specialize.

“I was interested in engineering, including the theoretical part of it,” Gupta says, “But I was always more interested in the applications: how to sell that technology or how it ties to the real world.”

After graduating in 2012, he moved overseas to attend the Hong Kong University of Science and Technology. The university offered a dual bachelor’s program that allowed him to earn one degree in industrial engineering and another in business management in just four years.

In his spare time, Gupta built a smartphone app that let students upload their class schedules and find classmates to eat lunch with. The app didn’t take off, he says, but he enjoyed developing it. He also launched Pulp Ads, a business that printed advertisements for student groups on tissues and paper napkins, which were distributed in the school’s cafeterias. He made some money, he says, but shuttered the business after about a year.

After graduating from the university in 2016, he decided to work in Hong Kong’s financial hub and joined Goldman Sachs as an analyst in the bank’s operations division.

From finance to process optimization at scale

After two parties agree on securities transactions, the bank’s operations division ensures that the trade details are recorded correctly, the securities and payments are ready to transfer, and the transaction settles accurately and on time.

As an analyst, Gupta’s task was to find bottlenecks in the bank’s workflows and fix them. He identified an opportunity to automate trade reconciliation: when analysts would manually compare data across spreadsheets and systems to make sure a transaction’s details were consistent. The process helped ensure financial transactions were recorded accurately and settled correctly.

Gupta built internal automation tools that pulled trade data from different systems, ran validation checks, and generated reports highlighting any discrepancies.

“Instead of analysts manually checking large datasets, the tools automatically flagged only the cases that required investigation,” he says. “This helped the team spend less time on repetitive verification tasks and more time resolving complex issues. It was also my first real exposure to how software and data systems could dramatically improve operational workflows.”

“Whether it’s helping a person improve a trait like that or driving efficiencies at a business, AI just has so much potential to help. I’m excited to be a little part of that.”

The experience made him realize he wanted to work more deeply in technology and data-driven systems, he says. He decided to return to school in 2018 to study data science and AI, when the fields were just beginning to surge into broader awareness.

He discovered that Columbia offered a dedicated master’s degree program in data science with a focus on AI. After being accepted in 2019, he moved to New York City.

Throughout the program, he gravitated to the applied side of machine learning, taking courses in applied deep learning and neural networks.

One of his major academic highlights, he says, was a project he did in 2019 with the Brown Institute, a joint research lab between Columbia and Stanford focused on using technology to improve journalism. The team worked with The Philadelphia Inquirer to help the newsroom staff better understand their coverage from a geographic and social standpoint. The project highlighted “news deserts”—underserved communities for which the newspaper was not providing much coverage—so the publication could redirect its reporting resources.

To identify those areas, Gupta and his team built tools that extracted locations such as street names and neighborhoods from news articles and mapped them to visualize where most of the coverage was concentrated. The Inquirer implemented the tool in several ways including a new web page that aggregated stories about COVID-19 by county.

“Journalism was an interesting problem set for me, because I really like to read the news every day,” Gupta says. “It was an opportunity to work with a real newsroom on a problem that felt really impactful for both the business and the local community.”

The GenAI inflection point

After earning his master’s degree in 2020, Gupta moved to San Francisco to join Asana, the company that developed the work management platform by the same name. He was drawn to the opportunity to work for a relatively small company where he could have end-to-end ownership of projects. He joined the organization as a product data scientist, focusing on A/B testing for new platform features.

Two years later, a new opportunity emerged: He was asked to lead the launch of Asana Intelligence, an internal machine learning team building AI-powered features into the company’s products.

“I felt I didn’t have enough experience to be the founding data scientist,” he says. “But I was also really interested in the space, and spinning up a whole machine learning program was an opportunity I couldn’t turn down.”

The Asana Intelligence team was given six months to build several machine learning–powered features to help customers work more efficiently. They included automatic summaries of project updates, insights about potential risks or delays, and recommendations for next steps.

The team met that goal and launched several other features including Smart Status, an AI tool that analyzes a project’s tasks, deadlines, and activity, then generates a status update.

“When you finally launch the thing you’ve been working on, and you see the usage go up, it’s exhilarating,” he says. “You feel like that’s what you were building toward: users actually seeing and benefiting from what you made.”

Gupta and his team also translated that first wave of work into reusable frameworks and documentation to make it easier to create machine learning features at Asana. He and his colleagues filed several U.S. patents.

At the time he took on that role, OpenAI launched ChatGPT. The mainstreaming of generative AI and large language models shifted much of his work at Asana from model development to assessing LLMs.

OpenAI captured the attention of people around the world, including Gupta. In September 2025 he left Asana to join OpenAI’s data science team.

The transition has been both energizing and humbling, he says. At OpenAI, he works closely with the marketing team to help guide strategic decisions. His work focuses on developing models to understand the efficiency of different marketing channels, to measure what’s driving impact, and to help the company better reach and serve its customers.

“The pace is very different from my previous work. Things move quickly,” he says. “The industry is extremely competitive, and there’s a strong expectation to deliver fast. It’s been a great learning experience.”

Gupta says he plans to stay in the AI space. With technology evolving so rapidly, he says, he sees enormous potential for task automation across industries. AI has already transformed his core software engineering work, he says, and it’s helped him enhance areas that aren’t natural strengths.

“I’m not a good writer, and AI has been huge in helping me frame my words better and present my work more clearly,” he says. “Whether it’s helping a person improve a trait like that or driving efficiencies at a business, AI just has so much potential to help. I’m excited to be a little part of that.”

Exploring IEEE publications and connections

Gupta has been an IEEE member since 2024, and he values the organization as both a technical resource and a professional network.

He regularly turns to IEEE publications and the IEEE Xplore Digital Library to read articles that keep him abreast of the evolution of AI, data science, and the engineering profession.

IEEE’s member directory tools are another valuable resource that he uses often, he says.

“It’s been a great way to connect with other engineers in the same or similar fields,” he says. “I love sharing and hearing about what folks are working on. It brings me outside of what I’m doing day to day.

“It inspires me, and it’s something I really enjoy and cherish.”

This article is crossposted from IEEE Spectrum’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free!

The Worst Engineer in the Room

My salary doubled. My confidence tanked.

That’s what happened when I had just joined a five-person startup in San Francisco in my third year as a software engineer. Two of the founders had been recognized in Forbes 30 Under 30. The team was exceptional by any measure.

On my first day, someone made a joke about Dijkstra’s algorithm. Everyone laughed. I smiled along, then looked it up afterward so I could understand why it was funny. Dijkstra’s algorithm finds the shortest path between 2 points—the math underlying GPS navigation. It’s a foundational concept in virtually every formal computer science curriculum. I had never encountered it.

That moment reflected a broader pattern. Conversations about system design and tradeoffs often felt just out of reach. I could follow parts of them, but not enough to contribute meaningfully.

I was mostly self-taught. Wide coverage, shallow roots. The engineers around me had roots. You could feel it in how they reasoned through problems, how they talked about tradeoffs, how they debugged with patience instead of pure panic.

The Advice That Sounds Good Until You’re Living It

You’ve heard the phrase: “If you’re the smartest person in the room, you’re in the wrong room.”

It sounds aspirational. What nobody tells you is what it actually feels like to be in that room. It feels like barely following system design conversations. Like nodding along to discussions you can only partially decode. Like shipping solutions through trial and error and hoping nobody looks too closely.

Being the weakest engineer in the room is genuinely uncomfortable. It surfaces every gap. And if you’re not careful, it pushes you in exactly the wrong direction.

My instinct was to make myself smaller. On a team of five, every voice mattered. I stopped offering mine. I rushed toward working solutions without real understanding, hoping velocity would compensate for depth.

I was working harder and, at the same time, I was not improving.

The turning point came when one of the most senior engineers left. Before departing, he told me it was difficult to work with me because I lacked foundational programming knowledge, listing out the concepts he saw me struggle with.

For the first time, what had felt like vague inadequacy became something specific.

What the Cliché Misses

Proximity to stronger engineers is not sufficient on its own. You won’t absorb their skill through osmosis. The engineers who thrive when they’re outmatched are not the ones who wait for confidence to arrive. They treat the discomfort as diagnostic information.

What can they answer that I can’t? What do they see in a system that I’m missing?

I defined a clear picture of the engineer I wanted to become and compared it to where I was. I wrote down what I did not know. I identified how I would close each gap with books, tutorials and small projects. I asked for recommendations from the same engineer who gave me the hard feedback.

I figured out the gaps. Then the bridges. Then I worked through each of them.

Over time, conversations became clearer. Debugging became more systematic. I started contributing meaningfully rather than just executing tasks.

The Other Room Nobody Warns You About

There’s a less-obvious version of this same problem: when you’re the strongest engineer in the room.

It can feel rewarding. Less friction, more validation. But there’s also less growth. When you’re at the ceiling, there’s no external pressure to raise your own floor. The feedback loops that sharpen judgment go quiet. Some engineers spend years there without noticing. They’re good. They’re comfortable. They stop getting better.

Both rooms carry risk. One threatens your confidence. The other threatens your trajectory.

Being the weakest engineer in a strong room is an advantage, but only if you treat it like one. It gives you a clear benchmark. But the room doesn’t do the work for you. You have to name the gaps, build a plan, and follow through.

And if you ever find yourself in the other room, where you’re clearly the strongest, pay attention to how long you’ve been there.

Both rooms are trying to tell you something.

—Brian

Are U.S. Engineering Ph.D. Programs Losing Students?

Not every engineer has a doctorate, but Ph.D. engineers are an essential part of the workforce, researching and designing tomorrow’s high-tech products and systems. In the United States, early signs are emerging that Ph.D. programs in electrical engineering and related fields may be shrinking. Political and economic uncertainty mean some universities are now seeing smaller applicant pools and graduate cohorts.

Read more here.

What Happens When You Host an AI Cafe

Last November, three professors at Auburn University in Ala. hosted a gathering at a coffee shop to confront students’ concerns about AI. The event, which they call an “AI Café,” was meant to create an environment “where scholars engage their communities in genuine dialogue about AI. Not to lecture about technical capabilities, but to listen, learn, and co-create a vision for AI that serves the public interest.” In a guest article, they share what they learned at the event and tips for starting your own AI Café.

Read more here.

What Is Inference Engineering?

Read more here.

Gerard “Gus” Gaynor, a long-serving IEEE volunteer and former engineering director at 3M, died on 9 March. The IEEE Life Fellow was 104.

Readers of The Institute might remember Gus from his 2022 profile: “From Fixing Farm Equipment to Becoming a Director at 3M.” Just last year, he and I coauthored twoarticles. One discusses how to leverage relationships to boost your career growth. The other weighs the pros and cons of pursuing a technical or managerial career path. He was 103 years old then. How many IEEE members can claim a centenarian coauthor?

I first met Gus in 2009 at the IEEE Technical Activities Board (TAB) meeting in San Juan, Puerto Rico. We sat together in the airplane on our way back to Minneapolis, our hometown. At home I told many of my friends about the remarkable person—who was 87 years young at the time—with whom I chatted during our six-hour flight.

A decade later, he and I met for lunch in Minneapolis. He drove himself to the restaurant, just asking for a hand to navigate the snowy sidewalk.

A dedicated IEEE volunteer

Gus’s involvement with IEEE predates the organization. He joined the Institute of Radio Engineers, a predecessor society, as a student member in 1942. Twenty years later he became an active IEEE volunteer.

He served on the TAB’s finance committee and the Publications Services and Products Board. He was president of the IEEE Engineering Management Society (now the Technology and Engineering Management Society ), and he was the Technology Management Council’s first president. He was the founding editor of IEEE-USA’s online magazine Today’s Engineer, which reported on government legislation and issues affecting U.S. members’ careers. The magazine is now available as the e-newsletter IEEE-USA InSight.

He authored several books on technology management and other topics, published by IEEE-USA and IEEE-Wiley.

IEEE Life Fellow Gerard “Gus” Gaynor died on 9 March.The Gaynor Family

Most recently, after the formation of TEMS in 2015, he became an active member of its executive committee. He served two terms as vice president of publications.

At 100 years old, he led the launch of a new publication, TEMS Leadership Briefs, a novel short-format open-access publication aimed at technology leaders.

Gus, who is a former member of The Institute’s editorial advisory board, also worked with Kathy Pretz, The Institute’s editor in chief, to start an ongoing series of TEMS-sponsored career-interest articles. He coauthored several of them.

Throughout his 64 years as an IEEE volunteer, he received several honors. They include IEEE EMS’s Engineering Manager of the Year Award, the IEEE TEMS Career Achievement Award, and the IEEE-USA McClure Citation of Honor. In 2014 he was inducted into the IEEE Technical Activities Board Hall of Honor.

A 25-year career at 3M

Gus received a degree in electrical engineering in 1950 from the University of Michigan in Ann Arbor. He worked for several companies including Automatic Electric (now part of Nokia) and Johnson Farebox (now part of Genfare), before joining 3M in 1962.

During his successful 25-year career at 3M, he served as chief engineer for a division in Italy, established the innovation department, and led the design and installation of the company’s first computerized manufacturing facilities. He retired as director of engineering in 1987.

Last year, IEEE Life Fellow Michael Condry, a former TEMS president, organized a Zoom call with Gus and other leaders of the society to celebrate Gus’s 104th birthday. Gus looked well and was his usual upbeat self, telling everyone: “I’m good. Everything’s well. I can’t complain.”

Gus was married to Shirley Margaret Karrels Gaynor, who passed away in 2018. He lives on in the hearts and minds of his seven children, seven grandchildren, two great-grandchildren, and innumerable friends and IEEE colleagues.

Kyle McGinley graduated from high school in 2018 and, like many teenagers, he was unsure what career he wanted to pursue. Recuperating from a sports injury led him to consider becoming a physical therapist for athletes. But he was skilled at repairing cars and fixing things around the house, so he thought about becoming an engineer, like his father.

McGinley, who lives in Sellersville, Pa., took some classes at Montgomery County Community College in Blue Bell, while also working. During his years at the college, he took a variety of courses and was drawn to electrical engineering and computing, he says. He left to pursue a bachelor’s degree in electrical and computer engineering in Philadelphia at Temple University, where he is currently a junior.

Kyle McGinley

MEMBER GRADE

Student member

UNIVERSITY

Temple, in Philadelphia

MAJOR

Electrical and computer engineering

The 26-year-old is also a teaching assistant and a research assistant at Temple. His research focuses on applying artificial intelligence to electrical hardware and robotics. He helped build an AI-integrated android companion to assist in-home caregivers.

Temple recognized McGinley’s efforts last year with its Butz scholarship, which is awarded annually to an electrical and computer engineering undergraduate with an interest in software development, AI development systems, health education software, or a similar field.

An IEEE student member, he is active within the university’s student branch.

“Dr. Brian Butz, the late professor emeritus, dedicated his research to artificial intelligence,” McGinley says. “The scholarship he and his wife Susan established helps allow students to pursue research in AI. Their generous donation has helped fund my research.”

Building a robot aide

McGinley is a teaching assistant for his digital circuit design course. In a class of 35 students, it can be a struggle for some to digest the professor’s words, he says.

“My job is to answer students’ questions if they are having problems following the professor’s lecture or are confused about any of the topics,” he says. “In the lab, I help students debug code or with hardware issues they have on the FPGA [field-programmable gate array] boards.”

He also conducts research for the university’s Computer Fusion Lab under the supervision of IEEE Senior Member Li Bai, a professor of electrical and computer engineering. McGinley writes software programs at the lab.

“In school, they don’t teach you how to communicate with people. They only teach you how to remember stuff. Working well with people is one of the most underrated skills that a lot of students don’t understand is important.”

One such assignment was working with the Temple School of Social Work at the Barnett College of Public Health to build a robot companion integrated with AI to assist individuals with Parkinson’s disease and their caregivers.

“I realized the need for this with my grandmother, when she was taking care of my grandfather,” he says. “It was a lot for her, trying to remember everything.”

Using the latest software and hardware, he and three classmates rebuilt an older lab robot. They installed an operating system and used Python and C++ for its control, perception, and behavior, he says. The students also incorporated Google’s Gemini AI to help with routine tasks such as scheduling medication reminders and setting alarms for upcoming doctor visits.

Kyle McGinley helped build an AI-integrated android to assist individuals with Parkinson’s disease and their caregivers.Temple University of Public Health

The AI-integrated android was intended to assist, not replace, the caregivers by handling the mental load of remembering tasks, he says.

“This was one of the cool things that drew me to working in the robotics field,” he says. “Something where AI could be used to help caregivers do simple tasks.

“My career ambition after I graduate is to gain real-world experience in the engineering industry to learn skills outside of academia, Long term, I want to do project management or work in a technical lead role, with the primary goal of creating impactful projects that I can be proud of.”

The benefits of a student branch

McGinley joined Temple’s IEEE student branch last year after one of his professors offered extra credit to students who did so. After attending meetings and participating in a few workshops, he found he really liked the club, he says, adding that he made new friends and enjoyed the camaraderie with other engineering students.

After the student branch’s board members got to know McGinley better, they asked him to become the club’s historian and manage its social media account. He also helps with event planning, creating and posting fliers, taking pictures, and shooting videos of the gatherings.

The branch has benefited from McGinley’s involvement, but he says it’s a two-way street.

“The biggest things I’ve learned are being held accountable and being reliable,” he says. “I am responsible for other people knowing what’s going on.”

Being an active volunteer has improved his communication skills, he says.

“Learning to clearly communicate with other people to make sure everyone is on the same page is important,” he says. “In school, they don’t teach you how to communicate with people. They only teach you how to remember stuff. Working well with people is one of the most underrated skills that a lot of students don’t understand is important.”

He encourages students to join their university’s IEEE branch.

“I know it can be scary because you might not know anyone, but it honestly can’t hurt you; it could actually benefit you,” he says. “Being active is going to help you with a lot of skills that you need.

“You’ll definitely get opportunities that you would have never known about, like a scholarship or working in the research lab. I would have never gotten these opportunities if I hadn’t shown up. Joining IEEE and being active is the best thing you can do for your career.”

This article was updated on 9 April 2026.

Abhishek Appaji has committed his career to bringing lifesaving technology to underresourced communities. The IEEE senior member weaves together artificial intelligence, biomedical engineering, deep learning, and neuroscience to make doctors’ jobs easier and to improve patient outcomes.

“The intersection of these fields is where the most impactful breakthroughs in diagnostic precision occur,” says Appaji, an associate professor of medical electronics engineering at the B.M.S. College of Engineering, in Bengaluru, India.

Abhishek Appaji

Employer

B.M.S. College of Engineering, in Bengaluru, India

Job title

Associate professor of medical electronics engineering

Member grade

IEEE senior member

Alma maters

B.M.S. College of Engineering; University of Visvesvaraya, in Bengaluru; Maastricht University, in the Netherlands

Many of his inventions have been deployed in remote areas of India, providing physicians with quality diagnostic tools, including an AI-powered machine that can scan retinas to detect medical conditions and a smart bed that continuously monitors a patient’s vital signs.

An active volunteer with the IEEE Young Professionals Bangalore Section, he has launched professional networking events, technology workshops, a mentorship program, and other initiatives.

For his “contributions to accessible AI-driven health care solutions and leadership in empowering young professionals,” Appaji is the recipient of this year’s IEEE Theodore W. Hissey Outstanding Young Professional Award. The honor is sponsored by the IEEE Photonics and Power & Energy societies as well as IEEE Young Professionals. The award is scheduled to be presented this month during the IEEE Honors Ceremony in New York City.

“This award represents a significant milestone in my career,” Appaji says. “It validates my core belief that our success as engineers is not solely measured by research outcomes or publications but by the tangible impact we have on lives through accessible technology and the quality of the next generation of leaders we empower.”

Developing a blood glucose measurement device

After earning a bachelor’s degree in engineering from B.M.S. in 2010, he joined the school as a lecturer in its medical electronics engineering department. At the same time, he pursued master’s degrees in bioinformatics at the University Visvesvarya College of Engineering, also in Bengaluru. He graduated in 2013 and continued to teach at B.M.S.C.E.

Four years later, Appaji signed up for the MIT Global Entrepreneurship Bootcamp, a two-week intensive hybrid program that includes webinars, online courses, and a five-day stay at MIT. It’s designed to give teams of aspiring entrepreneurs, innovators, and early-stage founders the structured mindset, tools, and frameworks they need to succeed.

Appaji says he discovered the program while researching opportunities in innovation.

“I had the technical expertise, but I needed a structured framework to transition my research from the laboratory to the market,” he says.

During the MIT boot camp, he and a team of four other participants were tasked with approaching a complex health care challenge. They developed a noninvasive blood glucose measurement device to manage gestational diabetes—a condition that causes high blood sugar and insulin resistance during pregnancy. When the program ended, Appaji and two of his Australia-based teammates continued their collaboration by founding Glucotek in Brisbane, Australia.

Inspired to continue his research in health care technology, Appaji pursued a doctorate in mental health and neurosciences at Maastricht University, in the Netherlands.

His thesis focused on computational methods to identify retinal vascular patterns.

“The patterns we analyze—including the curvature of the vessels, the angles at which they branch out, and their dimensions—reveal the health of the microvascular system,” he says. “With conditions like schizophrenia and bipolar disorder, microvascular changes mirror neurovascular changes in the brain.”

“My journey has shown me that IEEE is much more than a professional society; it is a global platform that allows me to collaborate with a diverse network of experts to solve local humanitarian challenges.”

Examining and measuring the retinal vascular system offers physicians a noninvasive way to examine neural changes, which can be biomarkers for psychiatric illnesses, he says.

To bring his idea to life, he collaborated with an ophthalmologist, a psychiatrist, and colleagues from his engineering school to develop a screening device. They also created and trained the AI models that analyze retinal images.

Ideas from his thesis led to the creation of the Smart Eye Kiosk, an AI-powered tool that scans the network of small veins that deliver blood to the inner retina. The tool monitors stress levels and mental health. It also screens for basic eye diseases such as diabetic retinopathy, as well as damage to retinal blood vessels caused by high blood sugar.

Retinal images also can reveal physiological changes in the brain associated with psychiatric disorders such as schizophrenia and bipolar disorder, Appaji says. The kiosk uses AI models to analyze measurements of the vasculature network, such as vessel thickness, which can be biomarkers for psychiatric conditions. Since mental illnesses can be linked to genetics, relatives of patients with schizophrenia and bipolar disorder were also invited to participate in a study funded by India’s Cognitive Science Research Initiative’s Department of Science & Technology. The clinical data from this study can pave the way for earlier, more accurate diagnoses.

“The biological basis for this is fascinating,” Appaji says. “The retina is the only place in the human body where the central nervous system and the vascular system can be visualized directly and noninvasively. Anatomically, the retina is an extension of the posterior part of the brain. Therefore, physiological changes in the brain are often reflected in the eyes.”

This kiosk was developed in collaboration with Tan Tock Seng Hospital and Nanyang Technological University, which was funded by Ng Teng Fong Healthcare Innovation Program.

He earned his Ph.D. in 2020 from Maastricht, and he received the Best Thesis Award from the university’s Mental Health and Neuroscience Research Institute. Appaji credits his time at the school for his multidisciplinary approach to developing medical devices.

“Having the perspectives of mentors from diverse fields was essential to help me move my research beyond theory into a data-driven diagnostic tool,” he says.

He was then named institutional coordinator of R&D at B.M.S. and later was promoted to be its head.

Abhishek Appaji working on a smart bed sensor that continuously monitors a patient’s vital signs without the use of wires or wearable sensors.Abhishek Appaji

A wireless smart bed to monitor vital signs

Appaji continues to develop technologies for patients who need them most. “I feel a deep need to bridge this gap and ensure innovations have a tangible impact on society,” he says. In addition to the Smart Eye Kiosk, he improved the performance of the sensors of the smart beds that continuously monitor a patient’s vital signs without the use of wires or wearable sensors. The beds help hospital staff check on their patients in a noninvasive way.

The project was done in collaboration with health AI company Dozee (Turtle Shell Technologies) in Bengaluru. The system measures mechanical microvibrations produced by the body in response to the ejection of blood into the aorta, which occurs with each heartbeat. A thin, industrial-grade sensor sheet is placed underneath the mattress. Additional funding is being provided by India’s Department of Science and Technology.

“These sensors are incredibly sensitive,” Appaji says. “They pick up minute mechanical tremors through the mattress material.”

The sensors detect the force of the patient’s heartbeat and the expansion and contraction of their chest during respiration. The vibrations are converted into electrical signals and analyzed using deep learning algorithms developed by Appaji and his team at the university in collaboration with Dozee.

The technology is used in more than 200 hospitals throughout India and in thousands of households, he says.

Mentoring budding entrepreneurs

Appaji is also executive director of the BMSreenivasiah Innovators Guild Foundation, dedicated to nurturing entrepreneurial talent among students and faculty across the BMS group of Institutions. A not-for-profit company promoted by the BMS Education Trust, BIG Foundation provides a structured ecosystem for innovation, incubation, and startup growth.

There, Appaji mentors budding entrepreneurs, offering advice on business plans, product pitches, marketing strategies, and licensing. Participants are students and faculty members.

The foundation has incubated more than 10 ventures, according to Appaji.

“The majority are centered on health care applications,” he says, “and have successfully secured backing from investors and seed funds.”

Taking IEEE’s mission to heart

Appaji was introduced to IEEE as an undergraduate when one of his professors encouraged him to volunteer for a conference sponsored by the IEEE Engineering in Medicine and Biology Society. He transcribed the seminars for session chairs, assisted with managing the talks, and helped answer attendees’ questions.

“That experience was transformative,” he recalls. “I was amazed to find myself in the same room with the speakers and scientists who had authored the very textbooks I was studying.

“It was then that I realized IEEE is far more than just technology and volunteering; it is a global platform for high-level networking with world-class scientists and technologists.”

Appaji has served in several IEEE leadership positions, including 2018–2019 chair of the Young Professionals Bangalore Section. He is now treasurer of the IEEE Education Society, chair of IEEE Computer Society Bangalore Chapter, member of the steering committee of IEEE DataPort, and serves on the IEEE Member and Geographic Activities and IEEE Educational Activities boards.

“What motivates me to remain active within IEEE is the profound alignment between my personal goals and the organizational mission of advancing technology for the benefit of humanity,” he says. “My journey has shown me that IEEE is much more than a professional society; it is a global platform that allows me to collaborate with a diverse network of experts to solve local humanitarian challenges.”

The organization has helped fund some of Appaji’s lifesaving work. During the COVID-19 pandemic, he received a grant from the IEEE Humanitarian Technologies Board and Region 10 to develop 3D-printed protective equipment for people in Bengaluru’s underserved communities. The virus spread quickly in the high-density areas, where social distancing was nearly impossible. The kits, which included a door opener to avoid high-touch surfaces and an elbow-operated soap dispenser, were sent to nearly 500 households.

“This work remains one of my most meaningful contributions to humanitarian technology,” Appaji says, “demonstrating how engineering can be rapidly deployed to protect vulnerable populations during a global crisis.”

He advises younger IEEE members to: “Say yes to taking on roles of responsibility. Don’t wait for a formal title to lead; instead, start by volunteering to do small, manageable tasks within your local chapter or section.”

“The networking opportunities and leadership skills you gain through these early responsibilities will shape your professional career far more than any textbook ever could.”

To stay competitive, many small businesses need advanced wireless communication networks, not only to communicate but also to leverage technologies such as artificial intelligence, the Internet of Things, and robotics. Often, however, the businesses lack the technical expertise needed to install, configure, and maintain the systems.

Bhaskara Rallabandi, who spent more than two decades working for major telecom companies, decided to use his expertise to help small businesses. Rallabandi, an IEEE senior member, is an expert certified by the International Council on Systems Engineering.

Invences

Cofounder

Bhaskara Rallabandi

Founded

2023

Headquarters

Frisco, Texas

Employees

100

In 2023 he helped found Invences, a telecommunications automation company headquartered in Frisco, Texas.

Invences services include designing, building, and installing data centers, as well as cost-effective and secure wireless, private, IoT, and virtual communications networks.

The company has set up systems for farms, factories, and universities in rural and urban areas including underserved communities. Its mission, Rallabandi says, is to “build autonomous, ethical, and sustainable networks that connect communities intelligently.”

For his work, he was recognized last year for “entrepreneurial leadership in founding and scaling a U.S.-based technology company, advancing innovation in 5G/6G and Open RAN [radio access network], shaping global standards, and inspiring future leaders through mentorship and community impact” with the IEEE-USA Entrepreneur Achievement Award for Leadership in Entrepreneurial Spirit.

Building a telecommunications career

He began his telecommunications career in 2009 as a manager and principal network engineer at Verizon’s Innovation Labs in Waltham, Mass. He and his team ran some of the earliest long-term evolution and evolved packet core performance trials. (LTE is the 4G wireless broadband standard for mobile devices. EPC is the IP-based, high-performance core network architecture for 4G LTE networks.)

That work at Innovation Labs, he says, was key to the development of the first 4G systems. It set the stage for scalable, interoperable broadband architectures that underpin today’s 5G and 6G designs.

“We built the first bridge between legacy and cloud-native networks,” he says.

He left in 2011 to join AT&T Labs in Redmond, Wash. As senior manager and principal solutions architect, he oversaw the design, integration, and testing of the company’s next-generation wireless systems. He also led projects that redefined automation of networks and set up cloud computing systems including FirstNet, the nationwide broadband network for first responders, and VoLTE, the first voice-over-video LTE for conducting video calls.

In 2018 Rallabandi was hired as a principal and a senior manager of engineering at Samsung Networks Division’s Technology Solutions Division, in Plano, Texas. He led the development of 5G virtualization and Open RAN initiatives, which enable more flexible, scalable, and efficient large network deployments and interoperability among vendors.

Designing networks for small businesses

Feeling that he wasn’t reaching his full potential in the corporate world, and to help small businesses, he opted to start his own venture in 2023 with his wife, Lakshmi Rallabandi, a computer science engineer. She is Invences’s CEO, and he is its founding principal and chief technology advisor.

Invences, which is self-funded and employs about 100 people, has more than 50 customers from around the world.

“I wanted to do something more interesting where I could use the knowledge I gained working for these big companies to fill the gaps they overlooked in terms of automation” for small businesses, he says. “I have a team of people who, combined, have 200 years of technology experience.”

The startup builds networks that simplify its clients’ operations and reduce their costs, he says.

Instead of duplicating how major telecom carriers build networks for dense urban areas, he says, his designs reimagine the network architecture to lower its complexity, costs, and operational overhead.

“Connectivity should not be a luxury. Rural communities deserve an infrastructure that fits their needs.”

The systems integrate new technologies such as Open RAN, virtualized RAN, digital twins, telemetry, and advanced analytics. Some networks also incorporate agentic AI, an autonomous system that runs independently of humans and uses AI agents that plan and act across the network. Digital twins evaluate the agent’s decisions before releasing them.

“Autonomy is not about removing humans from the loop,” Rallabandi says. “It is about giving systems the ability to manage complexity so humans can focus on intent and outcomes.”

Rallabandi also has worked on AI-driven telecom observability technologies designed to allow networks to detect anomalies and optimize performance automatically.

He has developed a virtual O-RAN innovation lab, where clients can test the interoperability of their 5G systems, try out their enhancements, run trials of future functions, and experiment with updates.

Invences partnered with Trilogy Networks to build the FarmGrid platform for farms in Fargo, N.D., and Yuma, Ariz. FarmGrid used private 5G networks, edge-computing AI, and digital twins to make the operations more efficient.

“The project connects farms with sensors, analytics platforms, and autonomous equipment to enable precision agriculture, water optimization, and real-time decision-making,” Rallabandi says.

IEEE Senior Member Bhaskara Rallabandi talks about partnering with Trilogy Networks to build the FarmGrid platform for farms in Fargo, N.D., and Yuma, Ariz.TECKNEXUS

Paying it forward through IEEE programs

Rallabandi says he believes staying involved with IEEE is important to his career development and a way to give back to the profession. He is a frequent invited speaker at IEEE conferences.

He is active with IEEE Future Networks and its Connecting the Unconnected (CTU) initiative. Members of the Future Networks technical community work to develop, standardize, and deploy 5G and 6G networks as well as successive generations.

CTU aims to bridge the digital divide by bringing Internet service to underserved communities. During itsannual challenge, Rallabandi works with the winning students, researchers, and innovators to help them turn their concepts into affordable, cost-effective options.

“CTU represents the best of IEEE,” he says. “It is about taking innovation out of conferences and into communities that need it the most.

“Connectivity should not be a luxury. Rural communities deserve an infrastructure that fits their needs.”

He participates in the recently launched IEEE Future Networks Empowerment Through Mentorship initiative, which helps innovators, entrepreneurs, and startups expand their companies by educating them about finance, marketing, and related concepts.

“IEEE gives me both a voice and a responsibility,” Rallabandi says. “We’re not just developing technology; we are shaping how humanity connects.”

In today’s technological landscape, the only constant is the rate of obsolescence. As engineers move deeper into the eras of 6G, ubiquitous artificial intelligence, and hyper-miniaturized electronics, a traditional degree is only a starting point.

To remain competitive in today’s job market, technical specialists must evolve into future-ready professionals by cultivating more than just niche expertise. Success now demands a high degree of adaptive intelligence and strategic communication, allowing specialists to translate complex data into actionable business decisions as industry shifts accelerate.

To bridge the gap between technical proficiency and organizational leadership, the IEEE Professional Development Suite offers training on programs designed to build the strategic competencies required to navigate today’s complex landscape. The suite provides deep technical dives into domains such as telecommunications connectivity and microelectronics reliability. Organizations can stay ahead of the curve through informed decision-making and a future-ready workforce.

Mastery of electrostatic discharge and 5G networks

Within the semiconductor sector, which is projected to become a US $1 billion industry by 2030, electrostatic discharge (ESD) is a major reliability challenge. Because even a microscopic, unnoticed discharge can compromise a semiconductor, ESD issues account for up to one-third of all field failures, according to the EOS/ESD Association.

IEEE’s targeted training—the online Practical ESD Protection Design certificate program—equips teams with technical protocols to mitigate the risks and ensure long-term hardware reliability. Specialized ESD training has become essential for chip designers and manufacturing professionals seeking to improve discharge control.

The interactive modules cover theory, real-world case studies, and practical mitigation techniques. The standards-based instruction is aligned with ANSI/ESD S20.20–21: Protection of Electrical and Electronic Parts and other industry guidelines.

As 5G network capabilities expand globally, so does the demand for engineers who can master the protocols and procedures required to manage complex telecommunications systems. The IEEE 5G/6G Essential Protocols and Procedures Training and Innovation Testbed, in partnership with Wray Castle, takes a deep dive into the 5G network function framework, registration processes, and packet data unit session establishment. The program is designed for system engineers, integrators, and technical professionals responsible for 5G signaling. Stakeholders such as network operators, equipment vendors, regulators, and handset manufacturers could find the program to be beneficial as well.

“The IEEE Professional Development Suite ensures that learners are not just keeping pace with change but helping to drive it.”

To bridge the gap between theory and practice, the course includes three months of free access to the IEEE 5G/6G Innovation Testbed. The secure, cloud-based platform offers a private, end-to-end 5G network environment where individuals and teams can gain hands-on experience with critical system signaling and troubleshooting.

Leadership training programs

Technical knowledge alone is not enough to climb the corporate ladder. To thrive today, engineering leaders must have a strategic vision and people-centric leadership skills.

The IEEE Leading Technical Teams training program focuses on the challenges of managing engineers in R&D environments and fostering creative problem-solving through an immersive learning experience. It’s designed for professionals who have been in a leadership position for at least six months. Participants can gain self-awareness.

The program includes a 360-degree assessment that gathers feedback about the individual from peers and direct reports to build a personalized development plan. The goal is to help technical professionals transition from high-performing individual contributors into leaders who drive innovation by inspiring their teams rather than just managing tasks.

Organizations can enroll groups of 10 or more to learn as a cohort—which can ensure that everyone stays on the same page while setting a training schedule that fits the team’s deadlines.

In collaboration with the Rutgers Business School, IEEE offers two mini MBA programs to bridge the gap between technical expertise and executive leadership. The programs offer flexibility to fit the demanding schedules of senior professionals. The online format lets participants engage with content as their time permits, while live virtual office hours with faculty provide opportunities for real-time interaction.

During the mini MBA for engineers 12-week curriculum, technical professionals master core competencies such as financial analysis, business strategy, and negotiation to effectively transition into management roles.

The mini MBA in artificial intelligence embeds AI literacy directly into business strategy rather than treating the technology as a standalone subject. Participants learn to evaluate AI through financial modeling and governance frameworks, gaining a practical foundation to lead initiatives that incorporate the technology.

The programs are offered to individuals as well as to organizations interested in training groups of 10 employees or more.

Earning credits that count

All the programs within the IEEE Professional Development Suite offer continuing education units and professional development hours.

Earning globally recognized credits provides a professional advantage, signaling a commitment to growth that often serves as a prerequisite for advancing into senior, lead, or principal roles. Additionally, the credits satisfy annual professional engineering license renewal requirements, ensuring practitioners remain compliant while expanding their capabilities.

Why curated content matters

Developed by IEEE Educational Activities, the training programs are peer-reviewed and built to align with industry needs. By focusing on upskilling (improving current skills) and reskilling (learning new ones), the IEEE Professional Development Suite ensures that learners are not just keeping pace with change but helping to drive it.

This article is crossposted from IEEE Spectrum’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free!

Engineers Aren’t Bad at Communication. They’re Just Speaking to the Wrong Audience.

There’s a persistent myth that engineers are bad communicators. In my experience, that’s not true.

Engineers are often excellent communicators—inside their domain. We’re precise. We’re logical. We structure arguments clearly. We define terms. We reason from constraints.

The breakdown happens when the audience changes.

We’re used to speaking in highly technical language, surrounded by people who share our vocabulary. In that environment, shorthand and jargon are efficient. But outside that bubble, when talking to executives, product managers, marketing teams, or customers, that same precision can be confusing.

The problem isn’t that we can’t communicate. It’s that we forget to translate.

If you’ve ever explained a critical issue or error to a non-technical stakeholder, you’ve probably experienced this: You give a technically accurate explanation. They leave either more confused than before, or more alarmed than necessary.

Suddenly you’re spending more time clarifying your explanation than fixing the issue.

Under pressure, we default to what we know best—technical detail. But detail without context creates cognitive overload. The listener can’t tell what matters, what’s normal, and what’s dangerous.

That’s when the “engineers can’t communicate” narrative shows up.

In reality, we just skipped the translation step.

The Writing Shortcut

One of the simplest ways to improve written communication today is surprisingly easy: Run your explanation through an AI model and ask, “would this make sense to a non-technical audience? Where would someone get confused?”

You can also say:

• “Rewrite this for an executive audience.”
• “What analogy would help explain this?”
• “Simplify this without losing accuracy.”

Large language models are particularly good at identifying jargon and offering alternative framings. They’re essentially translation assistants.

Analogies are especially powerful. If you’re explaining system latency, compare it to traffic congestion. If you’re describing technical debt, compare it to skipping maintenance on a house. If you’re explaining distributed systems, try using supply chain examples.

The goal isn’t to “dumb it down.” It’s to map the unfamiliar onto something familiar.

Before sending an email or report, ask yourself:

• Does this audience need to understand the mechanism, or just impact?
• Does this explanation help them make a decision?
• Have I defined terms they might not know?

Translation When Speaking

When speaking—especially in meetings or presentations—most engineers have one predictable habit: We speak too fast.

Nerves speed us up. Speed causes filler words. Filler words dilute authority.

To prevent that, follow a simple rule: Speak 10 to 15 percent slower than feels natural.

Slowing down cuts down the number of times you say “um” and “uh”, gives you time to think, makes you sound more confident, and gives the listener time to process.

Another rule: Say only what the audience needs to move forward.

Explain just enough for the person to make a decision. If you overload someone with implementation details when they only need tradeoffs, you’ve made their job harder.

The Real Skill

The key skill in communication is audience awareness.

The same engineer who can clearly explain a concurrency bug to a peer can absolutely explain system risk to an executive. The difference is framing, vocabulary, and context. Not intelligence.

In the age of AI, where code generation is increasingly commoditized, the ability to translate complexity into clarity is becoming a defining advantage.

Engineers aren’t bad communicators. We just have to remember that outside our bubble, translation is part of the job.

—Brian

How Robert Goddard’s Self-Reliance Crashed His Dreams

Robert Goddard launched the first liquid-fueled rocket 100 years ago, but his legacy still has relevant lessons for today’s engineers. Although Goddard’s headstrong confidence in his ideas helped bring about the breakthrough, it later became an obstacle in what systems engineer Guru Madhavan calls “the alpha trap.” Madhavan writes: “We love to celebrate the lone genius, yet we depend on teams to bring the flame of genius to the people.”

Read more here.

Redefining the Software Engineering Profession for AI

For Communications of the ACM, two Microsoft engineers propose a model for software engineering in the age of AI: Making the growth of early-in-career developers an explicit organizational goal. Without hiring early-career workers, the profession’s talent pipeline will eventually dry up. So, they argue, companies must hire them and develop talent, even if that comes with a short-term dip in productivity.

Read more here.

IEEE Launches Global Virtual Career Fairs

Looking for a job? Last year, IEEE Industry Engagement hosted its first virtual career fair to connect recruiters and young professionals. Several more career fairs are now planned, including two upcoming regional events and a global career fair in June. At these fairs, you can participate in interactive sessions, chat with recruiters, and experience video interviews.

Read more here.

“Can I get an interview?” “Can I get a job when I graduate?” Those questions came from students during a candid discussion about artificial intelligence, capturing the anxiety many young people feel today. As companies adopt AI-driven interview screeners, restructure their workforces, and redirect billions of dollars toward AI infrastructure, students are increasingly unsure of what the future of work will look like.

We had gathered people together at a coffee shop in Auburn, Alabama, for what we called an AI Café. The event was designed to confront concerns about AI directly, demystifying the technology while pushing back against the growing narrative of technological doom.

AI is reshaping society at breathtaking speed. Yet the trajectory of this transformation is being charted primarily by for-profit tech companies, whose priorities revolve around market dominance rather than public welfare. Many people feel that AI is something being done to them rather than developed with them.

As computer science and liberal arts faculty at Auburn University, we believe there is another path forward: one where scholars engage their communities in genuine dialogue about AI. Not to lecture about technical capabilities, but to listen, learn, and co-create a vision for AI that serves the public interest.

The AI Café Model

Last November, we ran two public AI Cafés in Auburn. These were informal, 90-minute conversations between faculty, students, and community members about their experiences with AI. In these conversational forums, participants sat in clusters, questions flowed in multiple directions, and lived experience carried as much weight as technical expertise.

We avoided jargon and resisted attempts to “correct” misconceptions, welcoming whatever emotions emerged. One ground rule proved crucial: keeping discussions in the present, asking participants where they encounter AI today. Without that focus, conversations could easily drift to sci-fi speculation. Historical analogies—to the printing press, electricity, and smartphones—helped people contextualize their reactions. And we found that without shared definitions of AI, people talked past each other; we learned to ask participants to name specific tools they were concerned about.

Organizers Xaq Frohlich, Cheryl Seals, and Joan Harrell (right) held their first AI Café in a welcoming coffee shop and bookstore. Well Red

Most important, we approached these events not as experts enlightening the masses, but as community members navigating complex change together.

What We Learned by Listening

Participants arrived with significant frustration. They felt that commercial interests were driving AI development “without consideration of public needs,” as one attendee put it. This echoed deeper anxieties about technology, from social media algorithms that amplify division to devices that profit from “engagement” and replace meaningful face-to-face connection. People aren’t simply “afraid of AI.” They’re weary of a pattern where powerful technologies reshape their lives while they have little say.

Yet when given space to voice concerns without dismissal, something shifted. Participants didn’t want to stop AI development; they wanted to have a voice in it. When we asked “What would a human-centered AI future look like?” the conversation became constructive. People articulated priorities: fairness over efficiency, creativity over automation, dignity over convenience, community over individualism.

The three organizers, all professors at Alabama’s Auburn University, say that including people from the liberal arts fields brought new perspectives to the discussions about AI. Well Red

For us as organizers, the experience was transformative. Hearing how AI affected people’s work, their children’s education, and their trust in information prompted us to consider dimensions we hadn’t fully grasped. Perhaps most striking was the gratitude participants expressed for being heard. It wasn’t about filling knowledge deficits; it was about mutual learning. The trust generated created a spillover effect, renewing faith that AI could serve the public interest if shaped through inclusive processes.

How to Start Your Own AI Café

The “deficit model” of science communication—where experts transmit knowledge to an uninformed public—has been discredited. Public resistance to emerging technologies reflects legitimate concerns about values, risks, and who controls decision-making. Our events point toward a better model.

We urge engineering and liberal arts departments, professional societies, and community organizations worldwide to organize dialogues similar to our AI Cafés.

We found that a few simple design choices made these conversations far more productive. Informal and welcoming spaces such as coffee shops, libraries, and community centers helped participants feel comfortable (and serving food and drinks helped too!). Starting with small-group discussions, where people talked with neighbors, produced more honest thinking and greater participation. Partnering with colleagues in the liberal arts brought additional perspectives on technology’s social dimensions. And by making a commitment to an ongoing series of events, we built trust.

Facilitation also matters. Rather than leading with technical expertise, we began with values: We asked what kind of world participants wanted, and how AI might help or hinder that vision. We used analogies to earlier technologies to help people situate their reactions and grounded discussions in present realities, asking participants where they have encountered AI in their daily lives. We welcomed emotions constructively, transforming worry into problem solving by asking questions like: “What would you do about that?”

Why Engineers Should Engage the Public

Professional ethics codes remain abstract unless grounded in dialogue with affected communities. Conversations about what “responsible AI” means will look different in São Paulo than in Seoul, in Vienna than in Nairobi. What makes the AI Café model portable is its general principles: informal settings, values-first questions, present-tense focus, genuine listening.

Without such engagement, ethical accountability quietly shifts to technical experts rather than remaining a shared public concern. If we let commercial interests define AI’s trajectory with minimal public input, it will only deepen divides and entrench inequities.

AI will continue advancing whether or not we have public trust. But AI shaped through dialogue with communities will look fundamentally different from AI developed solely to pursue what’s technically possible or commercially profitable.

The tools for this work aren’t technical; they’re social, requiring humility, patience, and genuine curiosity. The question isn’t whether AI will transform society. It’s whether that transformation will be done to people or with them. We believe scholars must choose the latter, and that starts with showing up in coffee shops and community centers to have conversations where we do less talking and more listening.

The future of AI depends on it.

U.S. doctoral programs in electrical engineering form the foundation of technological advancement, training the brightest minds in the world to research, develop, and design next-generation electronics, software, electrical infrastructure, and other high-tech products and systems. Elite institutions have long served as launchpads for the engineers behind tomorrow’s technology.

Now that foundation is under strain.

With U.S. universities increasingly entangled in political battles under the second Trump administration, uncertainty is beginning to ripple through doctoral admissions for electrical engineering programs. While some departments are reducing the number of spots available in anticipation of potential federal funding cuts, others are seeing their applicant pools shrink, particularly among international students, who make up a significant portion of their programs.

In 2024 alone, U.S. universities awarded more than 2,000 doctorates in electrical and computer engineering, according to data from the National Center for Science and Engineering Statistics. The number of computing Ph.D.s grew significantly in the 2010s, according to data from the National Academies, but there is still high demand for those with advanced degrees across academia, government, and industry. Now, some universities point to warning signs of waning enrollment.

Though not all engineers have Ph.D.s, if enrollment continues to shrink, fewer doctoral students could mean fewer engineers developing cutting-edge technology and training the next generation, potentially exacerbating existing labor shortages as global competition for tech talent intensifies.

Federal funding cuts affect admissions

Public universities in particular are feeling the strain because they rely heavily on federal grants to support doctoral students.

The University of California, Los Angeles, for instance, must fund Ph.D. students for the duration of a degree—typically five years. In August 2025, the U.S. government pulled more than US $580 million in federal grants over allegations that the university failed to adequately address antisemitism on campus during student protests. A federal judge has since ordered the funding to be restored, but faculty began to worry that research support could be clawed back without notice, says Subramanian Iyer, distinguished professor at UC Los Angeles’s department of electrical and computer engineering.

According to Iyer, departments across UC Los Angeles, including engineering, plan to scale back Ph.D. admissions this year. “The fear is that at some point, all this government money will be taken away,” Iyer says. “Lowering the admissions rate is just a way to prepare for that reality.”

In response to a request for comment, a spokesperson for the U.S. National Science Foundation—a major source of federal research funding at UC Los Angeles and elsewhere—said, “NSF recognizes the essential role doctoral trainees play in the nation’s engineering and STEM enterprise” and noted several of the foundation’s awards and programs that support graduate research.

Funding shocks may also force Pennsylvania State University to reshape future admissions decisions, according to Madhavan Swaminathan, head of Penn State’s electrical engineering department and director of the Center for Heterogeneous Integration of Micro Electronic Systems (CHIMES), a semiconductor research lab.

In 2023, the Defense Advanced Research Projects Agency (DARPA) and industry partners awarded CHIMES a five-year $32.7 million grant. But in late 2025, the agency pulled its final year of funding from the center, citing a shift in priorities from microelectronics to photonics, Swaminathan says. As a result, CHIMES’ annual budget, which supports research assistantships for roughly 100 engineering graduate students, the majority pursuing Ph.D.s, will fall from $7 million in 2026 to $3.5 million in 2027. If these constraints persist, Penn State’s engineering department may reduce the number of doctoral students it supports.

In a statement, a DARPA spokesperson told IEEE Spectrum: “Basic research is central to identifying world-changing technologies, and DARPA remains committed to engaging academic institutions in our program research. By design, a DARPA program typically lasts about 3 to 5 years. Once we establish proof of concept, we transition the technology for further development and turn our attention to other challenging areas of research.”

Penn State’s enrollment numbers reflect Swaminathan’s caution. He says the electrical engineering Ph.D. cohort shrank from 28 students in 2024 to 15 students in 2025. Applications show a similar pattern. After rising from 195 in 2024 to 247 in 2025, Ph.D. applications fell roughly 30 percent to 174 for the upcoming 2026 cohort, a sign that prospective students may be wary of applying to U.S. programs.

Immigration restrictions and application declines

In late January, the Trump administration announced it had paused visa approvals for citizens of 75 countries. Months earlier, the administration proposed new restrictions on student visas, including a four-year cap.

For Texas A&M University’s graduate electrical and computer engineering programs, up to 80 percent of applicants each year are international students, according to Narasimha Annapareddy, professor and head of the department. Annapareddy says applications for the fall 2026 Ph.D. cohort have dropped by roughly 50 percent.

Annapareddy says the United States is “sending a message that migration is going to be more difficult in the future.” Foreign students often pursue degrees in the U.S. not only for academic training, he says, but to build long-term careers and lives in the country. Fewer applications from international students mean that the university forgoes a “driven and hungry” segment of the applicant pool who are highly qualified in technical fields.

“The fear is that at some point, all this government money will be taken away.”— Subramanian Iyer, UC Los Angeles

At the University of Southern California, the decline is more moderate. The freshman Ph.D. class fell from about 90 students in 2024 to roughly 70 in 2025, a reduction of 22 percent, according to Richard Leahy, department chair of USC’s Ming Hsieh Department of Electrical and Computer Engineering.

While Leahy says applications are down modestly overall, domestic applications have increased by roughly 15 percent. Beyond immigration restrictions, international students, particularly from countries such as India and China, may be staying in their home countries as their technology sectors expand.

“A lot of those students that would normally have come to the U.S. are now taking very good jobs working in the AI industry and other areas,” Leahy says. “There are a lot more opportunities now.”

Workforce pipeline strains

Some faculty say shrinking cohorts could erode the tech workforce if the pattern continues.

At UC Los Angeles, Iyer describes a doctoral ecosystem built on a chain of mentorship. Among the roughly 25 students in his lab, senior doctoral students mentor junior Ph.D. candidates, who in turn guide master’s students and undergraduates. The system depends on overlapping cohorts. Reducing the number of students hired weakens that overlap and the trickle-down benefits of the mentorship model that keeps labs functioning.

The real benefit of the university system isn’t just the teaching but also “the community that you build,” Iyer says. “As you decrease admissions, this will disappear.”

At Penn State, Swaminathan points to specialization as key to a strong workforce. Many doctoral students train in semiconductor engineering, feeding expert talent into the domestic chip industry. If enrollment continues to shrink over the next few years, Swaminathan says, companies may need to hire students with bachelor’s or master’s degrees, who might lack the necessary skills required to design and innovate new chips.

“Without that specialization, there’s only so much one can do,” Swaminathan says.

The industry–academia gap

Not all departments are shrinking. At the University of Texas at Austin, overall enrollment has remained relatively steady, according to Diana Marculescu, chair of UT Austin’s Chandra Family Department of Electrical and Computer Engineering.

While she says recent fluctuations aren’t raising alarms, her concern lies more with alignment between research and industry. Doctoral students often train according to current grant priorities, she says. But by the time graduates enter the job market four to six years later, their specialization may not align neatly with open roles. That creates friction in the talent pipeline.

“That lack of connection might be problematic,” Marculescu says. She argues that closer collaboration between universities and the private sector could help create stronger feedback loops between hiring needs and academic research priorities.

For now, USC’s Leahy says Ph.D. graduates remain in high demand, and the current shifts have not yet translated into measurable workforce shortages. “We should be concerned about the number of Ph.D.s,” he says. “But there isn’t a crisis at this point.”

Mel Olken

Former executive director of the IEEE Power & Energy Society

Fellow, 92; died 9 January

Olken became the first executive director of the IEEE Power & Energy Society (PES) in 1995. In 2002 he left the position to serve as founding editor in chief of the society’s Power & Energy Magazine. Olken led the publication until 2016, when he retired.

After receiving a bachelor’s degree in engineering from the City College of New York, Olken was hired as an electrical engineer by American Electric Power, a utility based in Columbus, Ohio. He helped design coal, hydroelectric, and nuclear power plants. While at AEP, he was promoted to manager of the electrical generation department.

He joined IEEE in 1958 and became a PES member in 1973. An active volunteer, he chaired the society’s energy development and power generation committee and its technical council.

Olken was elected an IEEE Fellow in 1988 for “contributions to innovative design of reliable generating stations.”

He became an IEEE staff member in 1984 as society services director for IEEE Technical Activities. From 1990 to 1995 he served as managing director of Regional Activities group (now IEEE Member and Geographic Activities), before becoming PES executive director.

He received a PES Lifetime Achievement Award in 2012 for his “broad and sustained technical contributions to the development of power engineering and the power engineering profession.”

Stephanie A. Huguenin

Research scientist

IEEE member, 48; died 1 October

Huguenin was an administrative assistant in the physics and biophysics department at Augusta University, in Georgia. According to her Augusta obituary, she died of an illness acquired during her volunteer work in India.

She received a bachelor’s degree in engineering in 1999 from the College of Charleston, in South Carolina. During her senior year, she worked as a mathematics and science tutor at the Jenkins Orphanage (now the Jenkins Institute for Children), in North Charleston. After graduating, Huguenin traveled to India to volunteer at an orphanage run by the Mother Teresa Foundation.

Upon returning to the United States in 2001, Huguenin worked as a freelance research consultant. Three years later she was hired as a systems administrator and archivist by photographer Ebet Roberts in New York City. In 2010 she left to work as an operations strategist and technical consultant.

She earned a master’s degree in communication and research science in 2016 from New York University. While at NYU, she conducted experimental and theoretical research in Internet Protocol design and implementation as well as network security and management.

From 2020 to 2024 she was a research scientist at businesses owned by her family. She joined Augusta University in 2023.

She was a member of the IEEE Geoscience and Remote Sensing Society and the IEEE Systems Council.

Huguenin volunteered for the Internet Engineering Task Force, a standards development organization, and the American Registry for Internet Numbers. ARIN manages and distributes internet number resources such as IP addresses and autonomous system numbers.

The nonprofits she supported included the Coastal Conservation League, the Longleaf Alliance, the Lowcountry Land Trust, the Nature Conservancy, and Women in Defense.

The rapid ascent of artificial intelligence and semiconductor manufacturing has created a paradox: Industries are booming yet they face a critical shortage of skilled workers. Demand for data center technicians, fabrication facility workers, and similar positions is growing. There aren’t enough candidates with the right skill sets to fill the in-demand jobs.

Although those technical roles are essential, they don’t always require a four-year degree—which has paved the way for skills-based microcredentials. By partnering with higher education institutions and training providers, industry leaders are helping to design targeted skills programs that quickly turn learners into job-ready technical professionals.

The new standard for skills validation

Because microcredentials are relatively new, consistency is key. Through its credentialing program, IEEE serves as a bridge between academia and industry. Developed and managed by IEEE Educational Activities, the program offers standardized credentials in collaboration with training organizations and universities seeking to provide skills-based qualifications outside formal degree programs. IEEE, as the world’s largest technical professional organization, has more than 30 years of experience offering industry-relevant credentials and expertise in global standardization.

IEEE is setting the benchmark for skills-based microcredentials by establishing a framework that includes assessment methods, qualifications for instructors and assessors, and criteria for skill levels.

A recent collaboration with the University of Southern California, in Los Angeles, for example, developed microcredentials for USC’s semiconductor cleanroom program. USC heads the CA Dreams microelectronics innovation hub.

“The IEEE framework allows us to rapidly prototype training programs and adapt on the fly in a way that building new university courses—much less degree programs—won’t allow.” —Adam Stieg

IEEE worked with USC to create standardized skills assessments and associated microcredentials so that industry hiring managers can recognize the newly developed skills. The microcredentials help people with or without four-year degrees join the semiconductor industry as cleanroom technicians or as engineers with cleanroom experience.

IEEE also has partnered with the California NanoSystems Institute at the University of California, Los Angeles, to create skills-based microcredentials for its cleanroom protocol and safety program.

Best practices for designing microcredentials

Based on IEEE’s work designing microcredentials with USC, UCLA, and other leading academic institutions, three best practices have emerged.

1. Align with industry needs before design.

Collaborate with industry prior to starting the design process. There isn’t a one-size-fits-all approach. Workforce needs vary based on industry sector, company size, and geography. Higher education institutions and training providers build relationships with companies and industry groups to create effective microcredential programs and methods of assessment.

2. Build for flexibility.

Traditional academic cycles can be slow, but technology moves fast. A flexible skills-based microcredentials framework allows programs to create or pivot as new breakthroughs occur.

“Setting up a credit-bearing course is not easy. And in a rapidly changing environment, you need to pivot quickly,” says Adam Stieg, research scientist and associate director at UCLA’s CNSI. “IEEE skills-based microcredentials are a flexible way to keep up our curriculum aligned with an evolving technology landscape.”

Stieg’s team worked with IEEE to build a framework to create microcredentials for its cleanroom protocol and safety program, ensuring it kept pace with the industry’s evolution.

“The IEEE framework allows us to rapidly prototype training programs and adapt on the fly,” he says, “in a way that building new university courses—much less degree programs—won’t allow.”

3. Implement a continuous-feedback loop.

Many of the technical roles companies are looking to fill in emerging fields such as AI, cybersecurity, and semiconductors are still being developed or are quickly evolving. The rapidly changing landscape requires continual communications and feedback among higher education, training providers, and industry.

“We struggle to have feedback loops through the education system to the industry and back again,” says Matt Francis, president and CEO of Ozark Integrated Circuits, in Fayetteville, Ark. Francis, who has served as IEEE Region 5 director, is an IEEE volunteer who supports workforce development for the semiconductor industry.

Creating consistent feedback loops is critical for generating consensus on the skills sets needed for microcredential programs, experts say, and it allows providers to update assessments as new tools and safety protocols enter the workplace.

“If we start thinking about having training frameworks used within companies that are essentially on some sort of standard and align with a microcredential, we can start to build consensus,” Francis says.

Getting started

Through its credentialing program, IEEE is helping higher education and industry work together to bridge the technical workforce skills gap. Contact its team to learn how IEEE skills-based microcredentials can help you fill your workforce pipeline.

The America’s Talent Strategy: Building the Workforce for the Golden Age report, published last year by the U.S. Departments of Commerce, Education, and Labor, identified a significant engineering and skills gap. The 27-page report concluded that the shortage of talent in essential areas—including advanced manufacturing, artificial intelligence, cloud computing, and cybersecurity—poses significant risks to U.S. economic and technological leadership.

To help attract talent in those fields, the Labor Department last month introduced incentives for apprenticeships, including a US $145 million “pay for performance” grant program. The funding aims to develop registered apprenticeships in high-demand fields including artificial intelligence and information technology.

Reacting to the urgent national need for targeted workforce development were members of IEEE Young Professionals, led by Alok Tibrewala, an IEEE senior member. He is a cochair of the IEEE North Jersey Section’s Young Professionals group.

“As a software engineer, this impending shortage concerns me because I believe that the U.S. AI and cybersecurity skills gap would show up first in the early-career pipeline,” Tibrewala says. “Students will be entering the U.S. workforce without enough hands-on experience building secure AI-enabled enterprise and cloud systems, and this gap will persist without practical, mentor-led training before graduation.”

Tibrewala led a strategic planning session with representatives from the New Jersey Institute of Technology, IEEE Member and Geographic Activities, and IEEE Young Professionals to discuss holding an event that would provide practical, industry-relevant training by experts and IEEE leaders.

“I was able to establish a partnership with NJIT, recruit speakers, design the event’s agenda, and promote the event to ensure it was aligned with the strategy outlined in the workforce report,” he says. “This effort aligns with broader U.S. workforce development priorities focused on industry-driven skills training in critical technology areas.”

The IEEE Buildathon event was held on 1 November at NJIT’s Newark campus. More than 30 students and early-career engineers heard from 11 speakers. Through interactive workshops, live demonstrations, and networking opportunities, they left with practical, employer-aligned skills and clearer career pathways for AI-era skills-building.

Tibrewala chaired the event and also serves as chair of the IEEE Buildathon program.

Session takeaways

Region 1 Director Bala S. Prasanna, a life senior member, gave the keynote address. He emphasized the need for universities, industry practitioners, and IEEE volunteer leaders to collaborate on programs to enhance technical skills.

IEEE Member Kalyani Matey, cochair of the IEEE North Jersey Section’s Young Professionals, conducted a workshop on how to build one’s personal brand and a responsive network. Participants received valuable insights about résumé building, effective communication strategies, and enhancing their visibility and employability.

“Over time, this kind of structured, employer-aligned training will help increase confidence, employability, and technical readiness across the country. With sustained support, programs like the IEEE Buildathon can become a practical bridge from education to industry in the AI era.” —Alok Tibrewala

Tibrewala led the Unlocking AI’s Potential: Solving Big Challenges With Smart Data and IEEE DataPort session. The web-based DataPort platform allows researchers to store, share, access, and manage their research datasets in a single, trusted location. He discussed needed skills including AI literacy, strong data handling and dataset stewardship, and turning data into actionable insights.

Chaitali Ladikkar, a senior software engineer, delivered the insightful Brains Behind the Game seminar. Ladikkar, an IEEE member, highlighted the transformative impact AI is having on gaming and game engine technologies. She explained how AI is reshaping game development. She also covered how machine learning is being used for animation, faster content generation and testing of new titles. Her seminar received enthusiastic feedback from participants.

The Building Better Business Relationships DiSC workshop provided insights into enhancing professional relationships and communication within an engineering workforce. DiSC is a behavioral self-assessment used to understand an individual’s communication style and to adapt to others.

Participant experience and testimonials

The event received high praise from participants for its practical and industry-relevant content, according to Tibrewala.

“This training significantly enhanced my understanding and readiness for industry roles, filling gaps my regular academic coursework did not fully address,” said Humna Sultan, an IEEE student member who is a senior studying computer science at Stevens Institute of Technology, in Hoboken, N.J.

“The Buildathon was structured around real engineering challenge scenarios that deepened my understanding of AI and cloud technologies,” said Carlos Figueredo, an IEEE graduate student member who is studying data science at the University of Michigan, in Ann Arbor. “It boosted my confidence and practical skills essential for the industry.”

Bavani Karthikeyan Janaki said “it was incredible to see how technology and sustainability came together to drive real-world impact, thanks to the dedicated efforts of the organizers including Tibrewala, Matey, and the IEEE North Jersey Young Professionals.” Janaki is pursuing a master’s degree in computer and information science at Long Island University, in New York.

Funding and collaborative efforts

The Buildathon was made possible through grants from the IEEE Young Professionals group and funding from the IEEE North Jersey Section and IEEE Member and Geographic Activities. Their support shows how IEEE’s professional organizations can collaborate to address workforce needs by supporting the delivery of technical sessions that strengthen early-career pipelines.

Future plans and a call to action

Building on the event’s success, Tibrewala and Matey plan to make the IEEE Buildathon an ongoing initiative. They are exploring ways to expand it to additional university campuses and IEEE communities.

Tibrewala says they plan to refine the format based on participant feedback and lessons learned. To support consistent quality, he and Matey say, they are working on a playbook for organizers that will include a repeatable agenda, a workshop template, speaker guidelines, and post-event feedback forms.

The approach depends on continued coordination among host universities, local IEEE sections, and Young Professional volunteers, Tibrewala says.

“Enabling other groups to run similar events,” he says, “can help more students and early-career engineers gain practical exposure to AI, data, cloud, cybersecurity, and other key emerging technologies in a structured setting.

“Efforts like this help translate national workforce priorities into real training that students and early-career engineers can apply immediately to their projects. This also helps close the gap between classroom learning and the realities of building secure, reliable systems in production environments. Over time, this kind of structured, employer-aligned training will help increase confidence, employability, and technical readiness across the country.

“With sustained support, programs like the IEEE Buildathon can become a practical bridge from education to industry in the AI era.”

In 2025 IEEE launched its first virtual career fair to help strengthen the engineering workforce and connect top talent with industry professionals. The event, which was held in the United States, attracted thousands of students and professionals. They learned about more than 500 job opportunities in high-demand fields including artificial intelligence, semiconductors, and power and energy. They also gained access to career resources.

Hosted by IEEE Industry Engagement, the event marked a milestone in the organization’s expanding workforce development efforts to bridge the gap between academic training and industry needs while bolstering the technical talent pipeline, says Jessica Bian, 2025 chair of the IEEE Industry Engagement Committee. The IEC works to strengthen the connection with industry professionals, companies, and technology sectors through global career fairs, as well as its Industry Newsletter, AI-powered career guidance tools, and World Technology Summits, where industry leaders discuss solutions to societal challenges.

“We are bringing together companies, universities, and young professionals to help meet the demand for technical talent in critical sectors,” Bian says. “It is part of our commitment to preparing the next generation of innovators.”

The virtual career fairs are expanding to more IEEE regions this year. One was held last month for Region 9 (Latin America). One is scheduled next month for Region 8 (Europe, Middle East, and Africa) and another in May for Region 7 (Canada).

A global career fair is slated for June.

Registration information for all the fairs is available at careerfair.ieee.org.

Innovative recruitment events

The fairs, which use the vFairs virtual platform, provide interactive sessions with representatives from hiring companies, direct chats with recruiters, video interviews, and access to downloadable job resources. The features help remove geographic barriers and increase visibility for employers and job seekers.

The career fair platform features interactive engagement tools including networking roundtables, a live activity feed, a leaderboard, and a virtual photobooth to encourage participants to remain active throughout the day.

Bringing together thousands of professionals

STEM students participated in the U.S. and Latin America events, along with early-career professionals and seasoned engineers—almost 8,000 participants in all. They represented diverse fields including software engineering, AI, semiconductors, and power systems.

Siemens, Burns & McDonnell, and Morgan Stanley were among the dozens of companies that participated in the U.S. event. More than 500 internships, co-op opportunities, and full-time positions were promoted.

“I found the overall process highly efficient and the platform intuitive—which made for a great sourcing experience,” said a recruiter from Burns & McDonnell, a design and construction firm. “I was able to join a session, short-list several high-potential candidates, review their résumés, and initiate contact with a couple of them.

“I am optimistic that we will be able to extend at least one offer from this pipeline.”

Participating students described the fair as impactful.

“I gained valuable hiring insights from industry leaders, like Siemens, TRC Companies, and Schweitzer Engineering Laboratories,” said Michael Dugan, an electrical and computer engineering graduate student at Rice University, in Houston.

New tools elevating the candidate experience

Attendees had access to AI-guided job-matching tools and career development programs and resources.

Prior to the fair, registrants could use the IEEE Career Guidance Counselor, an AI-powered career advisor. The ICGC tool analyzes candidates’ skills and experience to suggest aligned roles and provides tailored professional development plans.

The ICGC also makes personalized recommendations for mentors, job opportunities, training resources, and career pathways.

Pre-event workshops and mock interview sessions helped participants refine their résumé, strengthen interview strategies, and manage expectations. They also provided tips on how to engage with recruiters.

“I gained valuable hiring insights from industry leaders, like Siemens, TRC Companies, and Schweitzer Engineering Laboratories.” —Michael Dugan, graduate student at Rice University, in Houston

During the Future Ready Engineers: Essential Skills and Networking Strategies to Stand Out at a Career Fair workshop, Shaibu Ibrahim, a senior electrical engineer and member of IEEE Young Professionals, shared networking strategies for career fairs and industry events as well as tips on preparation, engagement, and effective follow-up.

“The workshop offered advice that shaped my approach to the fair,” Dugan said. “It truly helped manage expectations and maximize my preparation.”

Learning more about IEEE

To help participants learn about IEEE and its volunteering opportunities, its societies and councils set up roundtables and technical community booths at the fairs. They were hosted by IEEE Technical Activities, IEEE Future Networks, and the IEEE Signal Processing Society.

“While exploring volunteer opportunities, I was excited to learn about IEEE Future Networks,” Dugan said. “Connecting with dedicated IEEE members, like Craig Polk, was a definite highlight.” Polk is an IEEE senior member and a senior program manager for IEEE Future Networks.

A commitment to career development

IEEE created the career fairs as free, accessible platforms for employers and job seekers to serve as a trusted bridge between companies seeking top technical talent and members dedicated to advancing their career. It is our responsibility to support them by connecting them with meaningful career opportunities.

In today’s unpredictable job landscape, IEEE is stepping up to help our talented members navigate change, build resilience, and connect with future employers.

EPICS in IEEE, a service learning program for university students supported by IEEE Educational Activities, offers students opportunities to engage with engineering professionals and mentors, local organizations, and technological innovation to address community-based issues.

The following two environmentally focused projects demonstrate the value of teamwork and direct involvement with project stakeholders. One uses smart biodigesters to better manage waste in Colombia’s rural areas. The other is focused on helping Turkish olive farmers protect their trees from climate change effects by providing them with a warning system that can identify growing problems.

No time to waste in rural Colombia

Proper waste management is critical to a community’s living conditions. In rural La Vega, Colombia, the lack of an effective system has led to contaminated soil and water, an especially concerning issue because the town’s economy relies heavily on agriculture.

The Smart Biodigesters for a Better Environment in Rural Areas project brought students together to devise a solution.

Vivian Estefanía Beltrán, a Ph.D. student at the Universidad del Rosario in Bogotá, addressed the problem by building a low-cost anaerobic digester that uses an instrumentation system to break down microorganisms into biodegradable material. It reduces the amount of solid waste, and the digesters can produce biogas, which can be used to generate electricity.

“Anaerobic digestion is a natural biological process that converts organic matter into two valuable products: biogas and nutrient-rich soil amendments in the form of digestate,” Beltrán says. “As a by-product of our digester’s operation, digestate is organic matter that can’t be transferred into biogas but can be used as a soil amendment for our farmers’ crops, such as coffee.

“While it may sound easy, the process is influenced by a lot of variables. The support we’ve received from EPICS in IEEE is important because it enables us to measure these variables, such as pH levels, temperature of the reactor, and biogas composition [methane and hydrogen sulfide]. The system allows us to make informed decisions that enhance the safety, quality, and efficiency of the process for the benefit of the community.”

The project was a collaborative effort among Universidad del Rosario students, a team of engineering students from Escuela Tecnológica Instituto Técnico Central, Professor Carlos Felipe Vergara, and members of Junta de Acción Comunal (Vereda La Granja), which aims to help residents improve their community.

“It’s been a great experience to see how individuals pursuing different fields of study—from engineering to electronics and computer science—can all work and learn together on a project that will have a direct positive impact on a community.” —Vivian Estefanía Beltrán

Beltrán worked closely with eight undergraduate students and three instructors—Maria Fernanda Gómez, Andrés Pérez Gordillo (the instrumentation group leader), and Carlos Felipe Vergara-Ramirez—as well as IEEE Graduate Student Member Nicolás Castiblanco (the instrumentation group coordinator).

The team constructed and installed their anaerobic digester system in an experimental station in La Vega, a town located roughly 53 kilometers northwest of Bogotá.

“This digester is an important innovation for the residents of La Vega, as it will hopefully offer a productive way to utilize the residual biomass they produce to improve quality of life and boost the economy,” Beltrán says. Soon, she adds, the system will be expanded to incorporate high-tech sensors that automatically monitor biogas production and the digestion process.

“For our students and team members, it’s been a great experience to see how individuals pursuing different fields of study—from engineering to electronics and computer science—can all work and learn together on a project that will have a direct positive impact on a community. It enables all of us to apply our classroom skills to reality,” she says. “The funding we’ve received from EPICS in IEEE has been crucial to designing, proving, and installing the system.”

The project also aims to support the development of a circular economy, which reuses materials to enhance the community’s sustainability and self-sufficiency.

Protecting olive groves in Türkiye

Türkiye is one of the world’s leading producers of olives, but the industry has been challenged in recent years by unprecedented floods, droughts, and other destructive forces of nature resulting from climate change. To help farmers in the western part of the country monitor the health of their olive trees, a team of students from Istanbul Technical University developed an early-warning system to identify irregularities including abnormal growth.

“Almost no olives were produced last year using traditional methods, due to climate conditions and unusual weather patterns,” says Tayfun Akgül, project leader of the Smart Monitoring of Fruit Trees in Western Türkiye initiative.

“Our system will give farmers feedback from each tree so that actions can be taken in advance to improve the yield,” says Akgül, an IEEE senior member and a professor in the university’s electronics and communication engineering department.

“We’re developing deep-learning techniques to detect changes in olive trees and their fruit so that farmers and landowners can take all necessary measures to avoid a low or damaged harvest,” says project coordinator Melike Girgin, a Ph.D. student at the university and an IEEE graduate student member.

Using drones outfitted with 360-degree optical and thermal cameras, the team collects optical, thermal, and hyperspectral imaging data through aerial methods. The information is fed into a cloud-based, open-source database system.

Akgül leads the project and teaches the team skills including signal and image processing and data collection. He says regular communication with community-based stakeholders has been critical to the project’s success.

“There are several farmers in the village who have helped us direct our drone activities to the right locations,” he says. “Their involvement in the project has been instrumental in helping us refine our process for greater effectiveness.

“For students, classroom instruction is straightforward, then they take an exam at the end. But through our EPICS project, students are continuously interacting with farmers in a hands-on, practical way and can see the results of their efforts in real time.”

Looking ahead, the team is excited about expanding the project to encompass other fruits besides olives. The team also intends to apply for a travel grant from IEEE in hopes of presenting its work at a conference.

“We’re so grateful to EPICS in IEEE for this opportunity,” Girgin says. “Our project and some of the technology we required wouldn’t have been possible without the funding we received.”

A purpose-driven partnership

The IEEE Standards Association sponsored both of the proactive environmental projects.

“Technical projects play a crucial role in advancing innovation and ensuring interoperability across various industries,” says Munir Mohammed, IEEE SA senior manager of product development and market engagement. “These projects not only align with our technical standards but also drive technological progress, enhance global collaboration, and ultimately improve the quality of life for communities worldwide.”

For more information on the program or to participate in service-learning projects, visit EPICS in IEEE.

On 7 November, this article was updated from an earlier version.