Sr. Principal Research Engineer Sunnyvale, California
Konstantin specializes in application of ML, AI and Reinforcement Learning to large scale real-world problems with domain focus on digital advertising, RTB, programmatic buying, forecasting and recommendations. His research interests include RL, policy gradient methods for policy optimization, recommender systems, streaming algorithms, optimum sampling and compression. Konstantin received Ph.D. degrees in Physics from University of Tennessee, Knoxville and M.S. from Moscow Institute of Physics and Technology in Russia. Before joining Yahoo! in 2009 he has worked as a researcher in academia at Stanford Linear Collider, Stanford on nonlinear QED physics experiments E144 and SSC Labs. He has also spent years developing enterprise data storage and security software as an architect and developer at a few startups in Silicon Valley.