MATLAB Central Blogs Feeds | MATLAB Central Blogs - MATLAB & Simulink Get the inside view on MATLAB & Simulink! https://blogs.mathworks.com Thu, 30 May 2019 13:19:08 +0000 en-US hourly 6 https://wordpress.org/?v=6.1.1 <![CDATA[From Differential Equations to Data: Exploring Inverse Problems with PINNLab]]>Tue, 15 Sep 2026 00:00:00 +0000

Guest writers: Mohan Parthasarathy and Padmanabhan Seshaiyer, PhD Mohan Parthasarathy is a student at Thomas Jefferson High School for Science and Technology. Padmanabhan Seshaiyer, PhD, is Professor of Mathematics at George Mason University.
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Guest writers: Mohan Parthasarathy and Padmanabhan Seshaiyer, PhD Mohan Parthasarathy is a student at Thomas Jefferson High School for Science and Technology. Padmanabhan Seshaiyer, PhD, is Professor of Mathematics at George Mason University.
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]]><![CDATA[TokaLab: An Open Access Virtual Tokamak for Education and Research]]>Mon, 14 Sep 2026 00:00:00 +0000

Mike's pick this week is TokaLab by Riccardo Rossi and the TokaLab Team. TokaLab was nominated by Temo Vekua.
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Mike's pick this week is TokaLab by Riccardo Rossi and the TokaLab Team. TokaLab was nominated by Temo Vekua.
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]]><![CDATA[The Real ROI of Simulation: Preventing Errors Before They Exist]]>Thu, 10 Sep 2026 00:00:00 +0000

In my previous blogs, I’ve emphasized the importance of simulation for early verification as the key ROI of Digital Engineering. I’ll be honest up front; this is a lie. But not for the reasons you think. In the post Bridging the Gap: Why Verification is the Missing Link in Your Digital Thread Strategy, we discussed how Model-Based Systems Engineering is a significant investment, and that simulating those models for early verification, or shift-left, is an essential aspect to achieving a return on that investment. This is true. In the post Automatic Code Generation: The Unbroken Link in the Digital Thread, we also discussed how leveraging automatic code generation from these same models to extend...

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In my previous blogs, I’ve emphasized the importance of simulation for early verification as the key ROI of Digital Engineering. I’ll be honest up front; this is a lie. But not for the reasons you think. In the post Bridging the Gap: Why Verification is the Missing Link in Your Digital Thread Strategy, we discussed how Model-Based Systems Engineering is a significant investment, and that simulating those models for early verification, or shift-left, is an essential aspect to achieving a return on that investment. This is true. In the post Automatic Code Generation: The Unbroken Link in the Digital Thread, we also discussed how leveraging automatic code generation from these same models to extend...

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]]><![CDATA[Startup Spotlight: safecubed Brings Technical Expertise to Safety-Critical Development]]>Wed, 09 Sep 2026 00:00:00 +0000

For companies developing safety-critical systems, building a working product is only part of the challenge. They also need to prove that the product is safe, reliable, and ready for certification. For many engineering teams, progress can slow at this stage as certification requirements expose gaps in documentation, validation, traceability, and system design. safecubed helps customers move from working systems to certifiable products. Founded by six engineers, the startup combines functional safety expertise with hands-on engineering knowledge. Today, the company supports customers across automotive, industrial, and transportation industries. A Foundation Years in the Making The founders of safecubed spent more than a decade working together on safety-critical engineering projects before launching the company. When their previous employer ceased operations, the team faced a decision. A customer who trusted their work chose to continue...

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For companies developing safety-critical systems, building a working product is only part of the challenge. They also need to prove that the product is safe, reliable, and ready for certification. For many engineering teams, progress can slow at this stage as certification requirements expose gaps in documentation, validation, traceability, and system design. safecubed helps customers move from working systems to certifiable products. Founded by six engineers, the startup combines functional safety expertise with hands-on engineering knowledge. Today, the company supports customers across automotive, industrial, and transportation industries. A Foundation Years in the Making The founders of safecubed spent more than a decade working together on safety-critical engineering projects before launching the company. When their previous employer ceased operations, the team faced a decision. A customer who trusted their work chose to continue...

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]]><![CDATA[Demystifying the Dark Art of Analog Design with Agentic AI]]>Tue, 08 Sep 2026 00:00:00 +0000

The word agent comes from the Latin verb agere, meaning “to do” or “to act.” In common parlance, an agent acts on behalf of another person or a group. However, the definition I find most useful is rooted in agency: the capacity to act or exert power. In that sense, Agentic AI is about giving AI delegated agency—enabling it to pursue goals, plan across steps, reason through tasks, use memory, and call external tools to execute workflows with increasing autonomy.

But how does one put AI agents to work effectively in engineering? Engineering is built on foundations of accuracy and determinism, both of which are things that Generative AI and LLMs regularly struggle with. Agentic AI offers another approach: enlist engineering tools with these key capabilities. Simulink has been used as a trusted design and simulation environment for engineering applications for decades and comes with the added advantage that it can clearly show

...

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The word agent comes from the Latin verb agere, meaning “to do” or “to act.” In common parlance, an agent acts on behalf of another person or a group. However, the definition I find most useful is rooted in agency: the capacity to act or exert power. In that sense, Agentic AI is about giving AI delegated agency—enabling it to pursue goals, plan across steps, reason through tasks, use memory, and call external tools to execute workflows with increasing autonomy.

But how does one put AI agents to work effectively in engineering? Engineering is built on foundations of accuracy and determinism, both of which are things that Generative AI and LLMs regularly struggle with. Agentic AI offers another approach: enlist engineering tools with these key capabilities. Simulink has been used as a trusted design and simulation environment for engineering applications for decades and comes with the added advantage that it can clearly show

...

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]]><![CDATA[How Clemson Students Built a 180 mph Driverless Racecar]]>Tue, 08 Sep 2026 00:00:00 +0000

This blog is in collaboration with University of Clemson's Deep Orange student development team and New Eagle.
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This blog is in collaboration with University of Clemson's Deep Orange student development team and New Eagle.
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]]> <![CDATA[OpenCode と Ollama で実現する、Mac 上の MATLAB によるローカル LLM 実行]]>Thu, 03 Sep 2026 00:00:00 +0000

※この投稿は 2026 年 8 月 20 日に The MATLAB Blog へ 投稿されたものの抄訳です。 --
Bio: オンラインコミュニティで活動する Toshi Takeuchi さんによるゲスト投稿です。Toshi はこの20年間、MathWorks で多くのマーケティング職を歴任してきました。
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※この投稿は 2026 年 8 月 20 日に The MATLAB Blog へ 投稿されたものの抄訳です。 --
Bio: オンラインコミュニティで活動する Toshi Takeuchi さんによるゲスト投稿です。Toshi はこの20年間、MathWorks で多くのマーケティング職を歴任してきました。
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]]> <![CDATA[Debugging Example: Wrong MAT-File Format Fix - Attempt 1]]>Thu, 03 Sep 2026 00:00:00 +0000

Here I try and debug a problem in a MATLAB Web App that was reported by one of my colleagues. I try and do a rather simple fix. See if you can determine why this attempt will not work. Features covered in this code-along style video include: save try, catch [bcvid id="6404495490112"] Play the video in full screen mode for a better viewing...

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Here I try and debug a problem in a MATLAB Web App that was reported by one of my colleagues. I try and do a rather simple fix. See if you can determine why this attempt will not work. Features covered in this code-along style video include: save try, catch [bcvid id="6404495490112"] Play the video in full screen mode for a better viewing...

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]]> <![CDATA[Agentic AI for 5G Engineering: Turning AI Assistants into Wireless Experts]]>Wed, 02 Sep 2026 00:00:00 +0000

The excitement around AI coding assistants is hard to overstate. Engineers use tools like GitHub Copilot, Claude Code, and OpenAI Codex every day to accelerate software development and automate routine tasks. But when it comes to wireless engineering, generating code is only part of the challenge.

Modern wireless systems involve complex standards, domain-specific conventions, simulation workflows, and validation processes that cannot be reduced to simple code completion. As Agentic AI emerges as the next evolution of AI-assisted engineering, a critical question arises: how do we transform a general-purpose AI assistant into a wireless engineering expert? This post explores the answer and demonstrates how MathWorks expert-curated tools and skills can turn AI assistants into capable engineering partners.

Why Wireless Engineering is Hard for AI

Large Language Models (LLMs) can be highly capable, but they remain prone to errors that are especially

...

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The excitement around AI coding assistants is hard to overstate. Engineers use tools like GitHub Copilot, Claude Code, and OpenAI Codex every day to accelerate software development and automate routine tasks. But when it comes to wireless engineering, generating code is only part of the challenge.

Modern wireless systems involve complex standards, domain-specific conventions, simulation workflows, and validation processes that cannot be reduced to simple code completion. As Agentic AI emerges as the next evolution of AI-assisted engineering, a critical question arises: how do we transform a general-purpose AI assistant into a wireless engineering expert? This post explores the answer and demonstrates how MathWorks expert-curated tools and skills can turn AI assistants into capable engineering partners.

Why Wireless Engineering is Hard for AI

Large Language Models (LLMs) can be highly capable, but they remain prone to errors that are especially

...

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]]><![CDATA[Learn MATLAB - A Student's Guide]]>Mon, 24 Aug 2026 00:00:00 +0000

In today’s blog, we have Ben Pasquariello from the Student Programs team at MathWorks. He’ll walk us through some helpful MATLAB resources and tips for getting started.Over to you, Ben...
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In today’s blog, we have Ben Pasquariello from the Student Programs team at MathWorks. He’ll walk us through some helpful MATLAB resources and tips for getting started.Over to you, Ben...
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]]><![CDATA[Running local LLMs with MATLAB using OpenCode and Ollama on a Mac]]>Thu, 20 Aug 2026 00:00:00 +0000

Bio: This is a guest post by Toshi Takeuchi, Community Advocate active in online communities. Toshi has held many marketing roles at MathWorks over the last 20 years
Do you have a modern M series Mac and are interested in a fully local agentic workflow with MATLAB?
no API keyno token costseverything stays local

Bio: This is a guest post by Toshi Takeuchi, Community Advocate active in online communities. Toshi has held many marketing roles at MathWorks over the last 20 years
Do you have a modern M series Mac and are interested in a fully local agentic workflow with MATLAB?
no API keyno token costseverything stays local

I talk about Model-Based Design a lot and in different forums: industries, universities, conferences. I usually position it as a way of ensuring our systems behave as we intended them to.
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I talk about Model-Based Design a lot and in different forums: industries, universities, conferences. I usually position it as a way of ensuring our systems behave as we intended them to.
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]]> <![CDATA[From HD Maps to Photorealistic Driving Video with RoadRunner, MATLAB, and NVIDIA Cosmos]]>Thu, 13 Aug 2026 00:00:00 +0000

This article is adapted from the presentation "Generating Input Videos for Cosmos Transfer Using RoadRunner/MATLAB" by the Application Engineering team at MathWorks Japan, delivered as part of the July 15, 2026 seminar.  

Collecting enough realistic data for automated driving and ADAS development can be challenging, especially for hazardous scenarios or difficult environmental conditions. A cut-in or emergency-braking event, for example, may need to be evaluated during the day, at night, in snow, or under strong sun glare.

A joint demonstration from Dynamic Map Platform (DMP), NVIDIA, and MathWorks explored another approach: define the driving scenario in simulation, then use generative AI to create photorealistic visual variations.

The workflow connects HD maps, RoadRunner, MATLAB and Simulink, and NVIDIA Cosmos-Transfer2.5 Auto Multiview:

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This article is adapted from the presentation "Generating Input Videos for Cosmos Transfer Using RoadRunner/MATLAB" by the Application Engineering team at MathWorks Japan, delivered as part of the July 15, 2026 seminar.  

Collecting enough realistic data for automated driving and ADAS development can be challenging, especially for hazardous scenarios or difficult environmental conditions. A cut-in or emergency-braking event, for example, may need to be evaluated during the day, at night, in snow, or under strong sun glare.

A joint demonstration from Dynamic Map Platform (DMP), NVIDIA, and MathWorks explored another approach: define the driving scenario in simulation, then use generative AI to create photorealistic visual variations.

The workflow connects HD maps, RoadRunner, MATLAB and Simulink, and NVIDIA Cosmos-Transfer2.5 Auto Multiview:

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]]><![CDATA[Trade Studies with Agentic-AI-powered MBSE]]>Wed, 12 Aug 2026 00:00:00 +0000

I was excited to see that my last post (Simulate in MATLAB, Animate in Blender) led to some remarkable follow-up responses. Vasilis (a winner of the 2025 Cody Contest) and Lubor both re-created my gantry crane scene despite the fact that I hadn't posted anything beyond an animation. And their simulations were much more elaborate than mine, featuring shattered walls and tumbling bricks! Scroll to the bottom of my post to see all the comments, but I'll include Vasilis's masterpiece here. A couple of days later, my blogging colleague Guy Rouleau posted his own Simscape Multibody version of the same scenario: 

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I was excited to see that my last post (Simulate in MATLAB, Animate in Blender) led to some remarkable follow-up responses. Vasilis (a winner of the 2025 Cody Contest) and Lubor both re-created my gantry crane scene despite the fact that I hadn't posted anything beyond an animation. And their simulations were much more elaborate than mine, featuring shattered walls and tumbling bricks! Scroll to the bottom of my post to see all the comments, but I'll include Vasilis's masterpiece here. A couple of days later, my blogging colleague Guy Rouleau posted his own Simscape Multibody version of the same scenario: 

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]]><![CDATA[STORX: Exploring Shape and Topology Optimization]]>Wed, 12 Aug 2026 00:00:00 +0000

George's pick this week is STORX by Amir Mirzendehdel (University of Kansas) and Krishnan Suresh (UW-Madison).
Say you've got some space to fill with material, a few places where the part is bolted down, and some forces pushing on it. You want a
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George's pick this week is STORX by Amir Mirzendehdel (University of Kansas) and Krishnan Suresh (UW-Madison).
Say you've got some space to fill with material, a few places where the part is bolted down, and some forces pushing on it. You want a
...

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]]> <![CDATA[Simulink-Based CAN Control and Validation on STM32F4 for a Dual-Motor EV Platform]]>Wed, 12 Aug 2026 00:00:00 +0000

In today’s blog, we are joined by Team I.C.C. from Inha University, South Korea. They share how they used MATLAB and Simulink to develop and validate a CAN-based embedded motor control workflow for their dual-motor EV platform. Over to you...
Introduction
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In today’s blog, we are joined by Team I.C.C. from Inha University, South Korea. They share how they used MATLAB and Simulink to develop and validate a CAN-based embedded motor control workflow for their dual-motor EV platform. Over to you...
Introduction
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]]><![CDATA[Responding to SR 26-2: From Strategic Interpretation to Practical Evidence | Part 4 of 4]]>Tue, 11 Aug 2026 00:00:00 +0000

When Monitoring Should Trigger Validation: A Practical SR 26-2 Case Study

How repeatable monitoring and validation evidence can support defensible model risk decisions.

Expert Contributor: Michael Belfanti

Michael is an Application Engineer at MathWorks focused on financial services. He works on credit risk analytics, model validation, and risk management workflows, drawing on prior experience in credit risk modeling and model governance at U.S. banks. He holds a PhD in Mathematics from The Ohio State University.

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When Monitoring Should Trigger Validation: A Practical SR 26-2 Case Study

How repeatable monitoring and validation evidence can support defensible model risk decisions.

Expert Contributor: Michael Belfanti

Michael is an Application Engineer at MathWorks focused on financial services. He works on credit risk analytics, model validation, and risk management workflows, drawing on prior experience in credit risk modeling and model governance at U.S. banks. He holds a PhD in Mathematics from The Ohio State University.

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]]><![CDATA[Building and Controlling a Gantry Crane with Simulink, Simscape Multibody, and Codex]]>Thu, 06 Aug 2026 00:00:00 +0000

A few days ago, my colleague Ned Gulley published this blog post: Simulate in MATLAB, Animate in Blender.

A few days ago, my colleague Ned Gulley published this blog post: Simulate in MATLAB, Animate in Blender.

The following post is from Sagar Hukkire, Senior Application Engineer at MathWorks, and Visa Suomi, Medical Devices Industry Manager.
Magnetic Resonance Imaging (MRI) reconstruction plays a critical role in transforming raw scanner data (in the frequency domain, known as k-space) into clinically usable images. In the examples shown here, we use low-SNR input k-space data from a T1-weighted MRI modality, which makes robust reconstruction
...

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The following post is from Sagar Hukkire, Senior Application Engineer at MathWorks, and Visa Suomi, Medical Devices Industry Manager.
Magnetic Resonance Imaging (MRI) reconstruction plays a critical role in transforming raw scanner data (in the frequency domain, known as k-space) into clinically usable images. In the examples shown here, we use low-SNR input k-space data from a T1-weighted MRI modality, which makes robust reconstruction
...

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