Sergey Levine

Assistant Professor at UC Berkeley

Sergey Levine is an Assistant Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He specializes in machine learning and robotics research, with a focus on developing algorithms that enable artificial intelligence systems and robots to acquire complex skills through learning and interaction.

Some key points about Sergey Levine:

Research Focus

Deep reinforcement learning
Robot learning and control
Computer vision for robotic perception
Unsupervised learning and generative models

Academic Background

PhD in Computer Science from Stanford University
BS and MS in Computer Science from Stanford University

Career Highlights

Assistant Professor at UC Berkeley since 2016
Research Scientist at Google Brain (2015-2016)
Postdoctoral researcher at UC Berkeley (2014-2015)

Notable Achievements

Recipient of multiple awards, including the NSF CAREER Award and the Sloan Research Fellowship
Published extensively in top AI and robotics conferences like NeurIPS, ICML, and RSS
Developed influential algorithms for robotic learning and control

Sergey Levine is considered a leading researcher in the field of robotic learning and reinforcement learning. His work aims to create AI systems and robots that can learn complex behaviors from raw sensory inputs, with applications in areas like robotic manipulation, autonomous driving, and general-purpose AI.