Pieter Abbeel is Professor and Director of the Robot Learning Lab at UC Berkeley [2008- ], Co-Director of the Berkeley AI Research (BAIR) Lab, Co-Founder of covariant.ai [2017- ], Co-Founder of Gradescope [2014- ], Advisor to OpenAI, Founding Faculty Partner of the AI@TheHouse venture fund, and Advisor to many AI/robotics start-ups. He works in machine learning and robotics. In particular, his research focuses on how to make robots learn from people (apprenticeship learning), how to make robots learn through their own trial and error (reinforcement learning), and how to speed up skill acquisition through learning-to-learn (meta-learning). His robots have learned advanced helicopter aerobatics, knot-tying, basic assembly, organizing laundry, locomotion, and vision-based robotic manipulation. He has won numerous awards, including best paper awards at ICML, NIPS, and ICRA, early career awards from NSF, Darpa, ONR, AFOSR, Sloan, TR35, and IEEE, and the Presidential Early Career Award for Scientists and Engineers (PECASE). Pieter’s work is frequently featured in the popular press, including the New York Times, BBC, Bloomberg, the Wall Street Journal, Wired, Forbes, Tech Review, and NPR.
robotics and machine learning with particular focus on deep reinforcement learning, deep imitation learning, deep unsupervised learning, meta-learning, learning-to-learn, and AI safety.