Martin J. Wainwright

Martin J. Wainwright is the Cecil H. Green Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Department of Electrical Engineering and Computer Science (EECS) and the Department of Mathematics. He is also associated with the Statistics and Data Science Center, the Laboratory for Information and Decision Systems, and the Institute for Data, Systems and Society. His research bridges machine learning, high-dimensional statistics, and information theory, with a focus on theoretical guarantees for algorithms in reinforcement learning, optimization, and graphical models.

• Books: High-Dimensional Statistics: A Non-Asymptotic Viewpoint (2019, Cambridge University Press), Statistical Learning with Sparsity: The Lasso and Generalizations (2015, CRC Press).
• Research Themes: Statistical and computational trade-offs, robustness in adaptive learning, posterior contraction rates, and decentralized estimation.

His recent work explores non-asymptotic analysis, stochastic approximation, and instance-dependent guarantees in reinforcement learning and optimization. Key contributions include minimax optimality in value estimation, variance-reduced Q-learning, and adaptive inference under elliptical constraints.

• Awards: IMS Medallion Lecturer, COPSS Presidents' Award, Loève Prize in Probability, Fellow of the Institute of Mathematical Statistics, NIPS Outstanding Paper Award.