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Dr. J. Andrew (Drew) Bagnell is an Assistant Research Professor at Carnegie Mellon University’s Robotics Institute and National Robotics Engineering Center (NREC) and is cross-appointed with the Machine Learning Department. His research focuses on machine learning for automated decision making, machine perception, adaptive control, optimization and planning under uncertainty. Some of Dr. Bagnell's key contributions include developing the first reinforcement learning algorithm for helicopter control, developing inverse optimal control methods for imitation learning in both field and legged robotics, and developing machine learning techniques for automated 2D/3D perception and control on programs ranging from commercial driver assistance to autonomous mining.
Dr. Bagnell received a B.Sc. in Electrical Engineering with highest honors from the University of Florida in 1998. He joined the Robotics Institute at Carnegie Mellon University in 2000 as a National Science Foundation Graduate Fellow, receiving an MS and PhD in Robotics in 2002 and 2004 respectively. He has spent the last decade working in machine learning and robotics, has over 30 peer-reviewed publications, and regularly serves on the senior program committee and as an associate editor in top conferences and journals in the field.
Artificial Intelligence, Machine Learning and Robotics: Interplay and Interaction
as author at 29th AAAI Conference on Artificial Intelligence, Austin 2015,
Imitation Learning and Purposeful Prediction: Probabilistic and Non-probabilistic Methods
as author at Probabilistic Approaches,