- Reinforcement learning
- 3D vision
- Optimal control
Animesh is an Assistant Professor of Computer Science at the University of Toronto and a Faculty Member at the Vector Institute where he leads the Toronto People, AI, and Robotics (PAIR) research group. Animesh is affiliated with Mechanical and Industrial Engineering (courtesy) and UofT Robotics Institute. Animesh also spend time as a research scientist at Nvidia Research in ML for Robotics. Prior to this, Animesh was a postdoc at Stanford AI Lab. Animesh earned a Ph.D. from UC Berkeley, an MS from Georgia Institute of Technology and a BE from the University of Delhi.
Animesh’s research focuses on machine learning algorithms for perception and control in robotics. Animesh aim’s to enable Generalizable Autonomy through efficient robot learning for long-term sequential decision making. The principal technical focus lies in understanding representations and algorithms to enable simplicity and generality of learning for interaction in autonomous agents. Animesh actively works on applications of robot manipulation in industrial and healthcare robotics.
- Nature Outlook, “Your robot surgeon will see you now“, Sept 2019.
- IEEE ICRA 2019 Best Paper Award
- IEEE IROS 2019 Best Paper in Cognitive Robotics Finalist
- IEEE ICRA 2019 Best Paper in Cognitive Robotics Finalist
- IEEE ICRA 2015 Best Medical Robotics Paper Award Finalist
- Hamlyn Surgical Robotics Challenge 2015 Best Video Demo Award
- IEEE ICRA 2012 Best Application Paper Award