Sergey Levine is a professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. His research focuses on machine learning for decision making and control, with an emphasis on deep learning and reinforcement learning algorithms, and 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. Applications of this work include autonomous robots and vehicles and computer vision and graphics. Sergey’s work has been featured in many popular press outlets, including the New York Times, the BBC, MIT Technology Review, and Bloomberg Business. Sergey holds a BS, MS, and PhD in computer science, all from Stanford University.
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