Elad Hazan

Elad Hazan is an Israeli-American computer scientist, academic, author and researcher. He is a professor of computer science at Princeton University, and the co-founder and director of Google AI Princeton.

Hazan co-invented adaptive gradient methods and the AdaGrad algorithm. He has published over 150 articles and has several patents awarded. He has worked machine learning and mathematical optimization, and more recently on control theory and reinforcement learning. He has authored a book, entitled Introduction to Online Convex Optimization. Hazan is the co-founder of In8 Inc., which was acquired by Google in 2018.

Education Hazan studied at Tel Aviv University and received his bachelor's and master's degrees in computer science in 2001 and 2002, respectively. He then moved to the United States, earning his doctoral degree in computer science from Princeton University in 2006 under Sanjeev Arora.

Research Hazan's research primarily focuses on machine learning, mathematical optimization, control theory and reinforcement learning. He is the co-inventor of five US patents.

Machine learning and mathematical optimization Hazan co-introduced adaptive subgradient methods to dynamically incorporate knowledge of the geometry of the data observed in earlier iterations, and to perform more informative gradient-based learning. The AdaGrad algorithm changed optimization for deep learning and serves as the basis for today's fastest algorithms. In his study, he also made substantial contributions to the theory of online convex optimization, including the Online Newton Step and Online Frank Wolfe algorithm, projection free methods, and adaptive-regret algorithms.

In the area of mathematical optimization, Hazan proposed the first sublinear-time algorithms for linear classification as well as semi-definite programming. He also gave the first linearly converging Frank-Wolfe-type algorithm.

More recently, Hazan and his group proposed a new paradigm for differentiable reinforcement learning called non-stochastic control, which applies online convex optimization to control.

Awards and honors 2002–2006 – Gordon Wu fellowship, Princeton University 2008 – Machine Learning Journal Award best student paper, COLT 2009, 2012 – IBM Pat Goldberg Memorial Best Paper Award 2011–2015 – European Research Council Marie Curie Fellow 2011, 2015 – Google Research Award 2012 – ICML Best Student Paper Runner Up 2013 – European Research Council (ERC) Starting Grant Recipient 2017 – Bell Labs Prize 2018 – Amazon Research Award