Dag Liodden, Co-Founder and CTO of Tapad, joined the Wikibon community to discuss the tools and technology that Tapad uses to make real-time decisions for ad placement.

Bio: Dag Liodden is Tapad’s co-founder and CTO. Dag oversees all technological advancements for the company, including Tapad’s notable breakthroughs in delivering targeted advertising across platforms. Prior to Tapad, he was the co-founder and CTO of Giant Leap Technologies AS, the premier Business Mobility solutions provider in the Nordic region. While there, Dag managed some of the largest wireless enterprise solution rollouts in Europe. He began programming at 6-years-old and has a Master’s Degree in Science, Industrial Economics and Technology Management from the Norwegian University of Science and Technology.

Bio: Adam is an Applied Researcher/Data Scientist who is currently employed in eBay’s NYC office. Adam has thus far had a stellar career, having worked as a Technology Analyst for Goldmann Sachs, a Software Engineer at CSC and a tech consultant for a range of companies such as Sun Microsystems. Dubbed as “one of the most hard working gifted people I know” by his associates, Adam clearly has proven his worth as an outstanding data scientist.

More on Scala and Hadoop:
Moving beyond object-oriented programming with Scala

Hadoop: Recent News From Mahout

Thumbtack: NoSQL Database Comparison by Ben Engber
 

Mike discusses the AppNexus infrastructure and their custom built continuous deployment system.

Bio: Mike oversees the Engineering and Technical Operations teams in AppNexus, having helped design the AppNexus system that handles over 12 billion ad requests a day. Prior to founding AppNexus, Mike was Director of Analytics and Product Manager at Right Media (acquired by Yahoo! for $850MM in July 2007), where he designed and managed key applications, including predictive optimization, inventory forecasting, and Media Guard, which protects publishers from harmful or unwanted ad content. Mike’s deep understanding of the intersection between business needs and technology innovation began at 15, when he sold his first software application, and continued at Princeton University, where he studied Economics. On his popular blog, MikeOnAds, Mike analyzes the fast-changing display ad management and buying space, and the dynamic interplay between ad networks, ad exchanges, real-time bidding and the entire ecosystem.

Steve will cover a variety of tools, both old and new, to measure, analyze and fix the performance of popular websites.

Bio: Steve is the Head Performance Engineer at Google where he works on web performance and open source initiatives. He previously served as Chief Performance Yahoo!. Prior to that Steve worked at General Magic, WhoWhere?, and Lycos, and co-founded Helix Systems and CoolSync. Steve is the author of High Performance Web Sites and Even Faster Web Sites. He is the creator of YSlow, one of the top 25 Firefox add-ons. He’s created numerous performance tools and services including the HTTP Archive, Cuzillion, Jdrop, ControlJS, and Browserscope. He serves as co-chair of Velocity, the web performance and operations conference from O’Reilly, and is co-founder of the Firebug Working Group. He taught CS193H: High Performance Web Sites at Stanford.

Bio: Mikael Ohlson is a software engineer and certified scrummaster from Stocklholm, Sweden, now living in NYC. Before he joined Spotify as an Android developer, Mikael was a system architect at TimeZynk AB, a startup in the field of mobile time reporting and related services. As the system architect, he aided the CTO in making decisions regarding architectural solutions for their mobile business tool and the server software that powered it, and then proceeded to implement the solutions.

In this talk, we’ll see how recommendation systems are created from data. What’s the algorithm? What’s the evaluation method? What’s the optimization procedure? When does it converge? We’ll talk about parallelizing in order to scale up to “big data” size via the MapReduce framework. Finally, we’ll think about priors and how they are overloaded. Content from this talk draws from chapters in Doing Data Science contributed by David Crawshaw and Matt Gattis.

Cathy O’Neil, PhD, Senior Researcher at Johnson Research Labs

Cathy O’Neil earned a Ph.D. in math from Harvard, was postdoc at the MIT math department, and a professor at Barnard College where she published a number of research papers in arithmetic algebraic geometry. She is co-authoring a book (with Rachel Schutt) called “Doing Data Science” to be published by O’Reilly in Spring 2013. She previously worked as a quant for the hedge fund D.E. Shaw in the middle of the credit crisis, and then for RiskMetrics, a risk software company that assesses risk for the holdings of hedge funds and banks. She facilitates an Occupy Wall Street working group, called Alternative Banking, and writes a blog at mathbabe.org.

We are having a talk by bit.ly on their recently open sourced data processing technology next Wednesday, come join us!

May 15th: Realtime Distributed Message Processing at Scale with NSQ
(Matt Reiferson from Bit.ly speaking)
http://www.meetup.com/NYC-Data-Engineering/events/113291272/

QCon New York is back!

http://qconnewyork.com/

QCon is a practitioner-driven conference designed for technical team leads, architects, engineering directors, and project managers who influence innovation in their teams. Some of the 15 tracks @QCon New York include: Polyglot Architectures, Applied Data Science, Java, Lean Startup Applied, Continuous Delivery, the JavaScript Ecosystem, Mobile Dev and more.

Pete Soderling, g33ktalk founder, will also be there, giving out hacks on how to get better at hiring as a software engineer, discover practical ways to build a unique engineering brand that will put your team at the top of the pack and develop better techniques for screening & interviewing engineers more quickly and effectively.

Don’t miss out!

Use promo code “g33ktalk″ to save $100!

http://qconnewyork.com/?utm_source=infoq&utm_medium=newsletter&utm_campaign=
g33ktalk

Today we will hear from SriSatish Ambati, founder of 0xdata (pronounced ‘hexadata’), which makes H2O, an opensource prediction and math engine for big data. He will be giving a talk on scaling GLM, Random Forest, and other popular big data algorithms such as the AllState Kaggle dataset.

Recorded at the SF Data Mining group’s recent H2O and streamdrill meetup hosted at Trulia.

SriSatish Ambati

Before founding 0xdata, SriSatish Ambati was the chief tinkerer of Java and Data stacks for the Cassandra Company, DataStax (formerly Riptano) & before that for 7 years at the JVM company, Azul Systems. Over the course of a decade or so, he has profiled, scaled and supported hundreds of in-production and in-development Java, enterprise and database stacks for performance. He uses these experiences to distil system trends and turbulences. SriSatish’s talks have been well received at conferences & tech fairs including JavaOne, JBossWorld & ApacheCon.

You can find more talks on big data here.

Simon Maynard will talk about debugging in Ruby, as well as the tools that Ruby gives you for error handling and how you can bend them to your will. He’ll also cover how errors will affect your Rack and Rails apps and show you how Rack middleware can help you deal with errors.

Simon Maynard is the CTO of Bugsnag, the leading application error monitoring service for Ruby.

This talk was recorded at the Silicon Valley Ruby Meetup at LinkedIn on April 2nd.