Google Research

Dave Anderson


Dave is currently an AI resident in Google NYC Research, where he started in June 2018. Dave’s current work focuses on initialization strategies of neural networks, with various applications including language modeling. This work has both theoretical and applied components. Dave pursued the residency because he was eager to apply his background in mathematics and numerical analysis to some of the most important problems in the world today. Thus far he has found the residency to be a fast-paced introduction to AI and a great opportunity to collaborate with many accomplished researchers in Research and Machine Intelligence. Dave aspires to continue a career in AI research after the residency. Dave completed a PhD in applied math from UC Berkeley in 2016. His research was on low rank approximation algorithms. His main result was a randomized LU decomposition with many benefits over the classic SVD algorithm. He graduated from the University of Pennsylvania in 2007, where he completed MA and BA degrees in mathematics and a BS degree from the Wharton School. He grew up in Denver, CO. Dave’s pastimes have varied over time and include scuba diving, volunteer ski patrol, weightlifting, cartooning, origami, and finding great lattes in New York City.

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