I am interested in the capability of robots and other agents to develop broadly intelligent behavior through learning and interaction.
Previously, I completed my Ph.D. in computer science at UC Berkeley and my B.S. in electrical engineering and computer science at MIT. I also spent time at Google as part of the Google Brain team.
Prospective students and post-docs, please see this page.
At NIPS 2017, we showcased our research on meta-imitation learning and visual foresight in a live robot demo! For more information and a video, see this page.
In summer 2017, I co-organized BAIR camp, a 2-day summer camp on human-centered AI for high-school students from low income backgrounds. We are organizing a second camp in August 2018.
My colleagues and I have released the robotic grasping and pushing data used in Levine et al. '16 (ISER) and Finn et al. '16 (NIPS): Google Brain Robotics Data.
Lecture videos for the Fall 2021 edition of CS330 are available online here.
In Fall 2019, I taught a new course on deep multi-task and meta learning. Lecture videos are available here.
At ICML 2019 and CVPR 2019, I gave an invited tutorial on Meta-Learning: from Few-Shot Learning to Rapid Reinforcement Learning. Slides, video, and references are linked here.
In December 2018, I gave a tutorial on model-based reinforcement learning at the CIFAR LMB program meeting (slides here).
In August 2017, I gave guest lectures on model-based reinforcement learning and inverse reinforcement learning at the Deep RL Bootcamp (slides here and here, videos here and here).
In Spring 2017, I co-taught a course on deep reinforcement learning at UC Berkeley. All lecture video and slides are available here.