Andrea Zanette

Andrea Zanette's research interests are in the foundations of reinforcement learning, a sub-area of machine learning that deals with decision-making under data-uncertainty.

Before joining CMU, he was a postdoctoral scholar in the Department of Electrical Engineering and Computer Sciences at UC Berkeley working with Martin Wainwright and Peter Bartlett. He completed his Ph.D. (2017-2021) in the Institute for Computational and Mathematical Engineering at Stanford University advised by prof Emma Brunskill and Mykel J. Kochenderfer, and has spent time collaborating with the labs of Facebook Artificial Intelligence Research and Microsoft Research.

His Ph.D. dissertation investigated modern reinforcement learning challenges such as exploration, function approximation, adaptivity, and learning from offline data; it was awarded the Gene Golub Outstanding Dissertation Award from his department. Zanette has a bachelor degree in mechanical engineering.