Nick Rhinehart is a Postdoctoral Scholar at UC Berkeley, where he works with Sergey Levine. He is broadly interested in the fields of machine learning, computer vision, robotics, and specifically interested in the topics of imitation learning, deep conditional generative models, reinforcement learning, and planning. Nick's research aims to build highly capable autonomous systems that learn to both accurately forecast outcomes and reliably use this understanding to make good decisions in new situations. He received a Ph.D. in Robotics from Carnegie Mellon University, where worked with Kris Kitani and was awarded a fellowship from the CMU School of Computer Science's Center of Machine Learning and Health. Nick's work received the Best Paper Honorable Mention Award at ICCV 2017 and the Best Paper Award at the ICML 2019 Workshop on AI for Autonomous Driving. He received undergraduate degrees in Engineering and Computer Science from Swarthmore College.