Max Simchowitz
About MeI am a postdoc in Russ Tedrake's Robot Locomotion group at MIT. My current work focuses on the theoretical foundations of learning for robotics and how to operationalize these insights in practical algorithms; this research has motivated a parallel interest in learning and extrapolation under distribution shift. My current work draws on past research ranging broadly across topics in adaptive sampling, multi-arm bandits, complexity of convex and non-convex optimization, reinforcement learning, learning in linear and nonlinear dynamical systems, and fairness in machine learning. I received my PhD in the EECS department at UC Berkeley, co-advised by Ben Recht and Michael Jordan, where I was generously supported by Open Philanthropy, NSF GRFP grant and Berkeley Fellowship grants. Previously, I recieved a BA in Mathematics at Princeton University, where I was fortunate enough to do research with Sanjeev Arora and David Blei (who taught at Princeton at the time). I am applying for academic faculty positions this 2023-2024 cycle. Selected Works
TeachingCS 189/289A, Introduction to Machine Learning, UC Berkeley Fall 2018 (TA). EE227C, Convex Optimization and Approximation, UC Berkeley, Spring 2018 (TA). Link for course notes. |