PEDLS Jitendra Malik — Lecture
| Event Date: | April 6, 2023 |
|---|---|
| Speaker: | Jitendra Malik, Arthur J. Chick Professor of EECS, UC Berkeley |
| Time: | 11:00-12:00 PM EST |
| Location: | ARMS Atrium |
| Priority: | No |
| School or Program: | Electrical and Computer Engineering |
| College Calendar: | Show |
Abstract
Deep learning has resulted in remarkable breakthroughs in fields such as speech recognition, computer vision, natural language processing, and protein structure prediction. Robotics has proved to be much more challenging as there are no pre-existing repositories of behavior to draw upon; rather the robot has to learn from its own trial and error in its own specific body, and it has to generalize and adapt. To make this feasible, we have developed “Rapid Motor Adaptation”, a novel technique for adaptive control in the framework of deep reinforcement learning. Using this, we can train robots in simulation and then transfer the skills directly to robots in the real world. I will show multiple examples – quadruped legged locomotion, biped locomotion, in-hand rotation, flying quadcopters – of the success of this approach. I will also show examples of life-long learning in robotics, by continuous adaptation of perception and action in deployed systems.
Biography
Jitendra Malik is the Arthur J. Chick Professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. He is also part-time Research Scientist Director at Meta. Malik's research group has worked on many different topics in computer vision, human visual perception, robotics, machine learning and artificial intelligence. Several well-known concepts and algorithms arose in this research, such as anisotropic diffusion, normalized cuts, high dynamic range imaging, shape contexts and R-CNN. His honors include the 2013 IEEE PAMI-TC Distinguished Researcher in Computer Vision Award, the 2014 K.S. Fu Prize from the International Association of Pattern Recognition, the 2016 ACM-AAAI Allen Newell Award, the 2018 IJCAI Award for Research Excellence in AI, and the 2019 IEEE Computer Society Computer Pioneer Award. He is a member of the National Academy of Engineering and the National Academy of Sciences, and a fellow of the American Academy of Arts and Sciences.
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