Data Scientists Meetup
Details
Plenty of food and beer as always. Co-sponsored by ThoughtBot.
Please RSVP so that we can get your name on the building list and you can come up quickly.
Food starts at 6:30pm. Talks start at 7, with short 5-10 minute talks by the speakers below.
Scheduled Talks:
• Theo Vassilakis - The technology and culture of big data analytics
• Chris Pouliot - New Challenges in Data Science: Geospatial Analysis
• Sean Gerrish - Topic models Models, Predicting Congressional Votes, and other Miscellany
• Varun Ganapathi - Terminal.com and iPython Notebook for data scientists
• John Myles White - A brief overview of the state of the Julia programming language, which is about to reach its 0.3 release in the next few weeks
• Chris Diehl - Data Science in Complex Environments - Needs and Design Challenges
• Joseph Reisinger - What can micro data tell us about macroeconomics?
• Gungor Polatkan - Laws of nature are simple and simple solutions are the best to complex problems
• Doug Beeferman - Realtime machine learning for fraud detection
Bios of the speakers:
• Theo Vassilakis is a founder and CEO of Metanautix. Prior to founding Metanautix, Theo spent nearly eight years at Google, most recently as a Principal Engineer and Engineering Director of a 75 engineer team in data warehousing, visualization, and analysis. He led the development ofDremel (http://research.google.com/pubs/pub36632.html) , a large-scale, interactive ad hoc query engine for big data processing that powers Google’s BigQuery (https://developers.google.com/bigquery/) , as well asTenzing (http://research.google.com/pubs/pub37200.html) , a SQL implementation on MapReduce. Theo also worked on developing large-scale machine learning systems for personalized search ads, audience analysis systems for display ads, and early prototypes of page preview and results-as-you-type for search.
Before Google, Theo was a software engineer at Microsoft and Microsoft Research, building data cleaning features for SQL Server and speech recognition models for Windows and Office. He holds a PhD from Brown University and a BS from Stanford University, both in Mathematics.
• Chris Pouliot is the Vice President of Data Science at Lyft, where he leads a team of Data Scientists whose charter is to help add statistical firepower to some of Lyft’s more complex analyses and algorithms. Previously he was the Director of Algorithms and Analytics at Netflix and a statistician at Google.
• Sean Gerrish is an engineering manager and technical lead of an analysis team at Google, and before that an engineer at Sift Science. Sean received a PhD in machine learning from Princeton University.
• John Myles White works at Facebook, where he’s a member of the Core Data Science team. He’s also been one of the main contributors of statistical software to Julia.
• Chris Diehl is a principal and co-founder of The Data Guild, a mission-driven data product studio based in Palo Alto.
• Joseph Reisinger is an engineer and data hacker exploring the intersection of econometrics and machine learning. He holds a PhD in Computer Science from UT Austin and spent his academic career building natural language understanding systems at Google Research and IBM T.J. Watson. Prior to co-founding Premise, he was Chief Scientist at Metamarkets.
• Gungor Polatkan is a Senior Data Scientist at Twitter. He has a PhD in Machine Learning from Princeton University. Before Twitter, he had several visiting/intern positions at places like Google, MERL and UC Berkeley.
• Doug Beeferman is a software engineer at Sift Science where he works on feature extraction and machine learning for fraud detection. Before this, Doug was an engineer at Google and Lycos.