Andrea Zanette is a PhD candidate in the Institute for Computational and Mathematical Engineering at Stanford University advised by prof Emma Brunskill and Mykel J. Kochenderfer. He also works closely with Alessandro Lazaric from Facebook Artificial Intelligence Research. His research focuses on provably efficient methods for Reinforcement Learning, in particular, he develops agents capable of autonomous exploration that 1) can leverage problem dependent structure and 2) can use function approximators. His research is currently supported by Total.
- Theory of Reinforcement Learning, Fall 2020. Visiting Graduate Student.