Animesh Garg

Animesh Garg is a CIFAR Chair Assistant Professor of Computer Science and Mechanical Engineering (courtesy) at the University of Toronto, a Faculty Member at the Vector Institute and UofT Robotics Institute, where he leads the Toronto People, AI, and Robotics (PAIR) research group. Animesh is also a Senior Researcher at Nvidia Research. Animesh earned a Ph.D. from UC Berkeley and was a postdoc at the Stanford AI Lab. His research focuses on machine learning algorithms for perception and control in robotics. His work aims to build Generalizable Autonomy in robotics which involves a confluence of representations and algorithms for reinforcement learning, control, and perception. His work has received AAAI New Faculty Highlight and Best Paper Recognitions at top tier venues in Machine Learning and Robotics  such as ICRA, IROS, RSS, Hamlyn Symposium, Workshops at NeurIPS, ICML, and has been widely covered in the press New York Times, Nature, Wired, IEEE Spectrum.

• Reinforcement learning
• Robotics
• Computer vision
• Causal Inference
• Geometric deep learning