Sergey Levine
Assistant ProfessorInfo Links
Research Areas
Artificial Intelligence (AI)Control, Intelligent Systems, and Robotics (CIR)
Research Centers
Berkeley Artificial Intelligence Research Lab (BAIR)CITRIS People and Robots (CPAR)
Berkeley Deep Drive (BDD)
Teaching Schedule
Fall 2020
CS 285. Deep Reinforcement Learning, Decision Making, and Control, MoWe 5:30PM - 6:59PM, Internet/OnlineSpring 2021
CS W182. Designing, Visualizing and Understanding Deep Neural Networks, MoWe 5:30PM - 6:59PM, Internet/OnlineCS 282A. Designing, Visualizing and Understanding Deep Neural Networks, MoWe 5:30PM - 6:59PM, Internet/Online
Biography
Sergey Levine received a BS and MS in Computer Science from Stanford University in 2009, and a Ph.D. in Computer Science from Stanford University in 2014. He joined the faculty of the Department of Electrical Engineering and Computer Sciences at UC Berkeley in fall 2016. His work focuses on machine learning for decision making and control, with an emphasis on deep learning and reinforcement learning algorithms. Applications of his work include autonomous robots and vehicles, as well as computer vision and graphics. His research includes developing algorithms for end-to-end training of deep neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, deep reinforcement learning algorithms, and more.Education
2014, Ph.D., Computer Science, Stanford University2009, B.S/M.S., Computer Science, Stanford University
Awards, Memberships and Fellowships
Sloan Research Fellow, 2019NSF Faculty Early Career Development Award (CAREER), 2017
MIT Tech Review Top 35 Innovators Under 35 (TR35), 2016
Office of Naval Research Young Investigator, 2016