PAIR

PAIR Lab is directed by Animesh Garg in the School of Interactive Computing at Georgia Tech Before moving to GT, we were at the Department of Computer Science at the University of Toronto.

Our research vision is to build the Algorithmic Foundations for Generalizable Autonomy, that enables robots to acquire skills, at both cognitive & dexterous levels, and to seamlessly interact & collaborate with humans in novel environments. We focus on understanding structured inductive biases and causality on a quest for general-purpose embodied intelligence that learns from imprecise information and achieves flexibility & efficiency of human reasoning.

Research: Our current research focuses on machine learning algorithms for perception and control in robotics. The principal focus of this research is to understand representations and algorithms to enable the efficiency and generality of learning for interaction in autonomous agents. We work on challenging open problems at the intersection of computer vision, machine learning, and robotics. We develop algorithms and systems that unify reinforcement learning, control theoretic modeling, causality, and 2D/3D visual scene understanding to teach robots to perceive and to interact with the physical world. Read more

If you are interested in joining us, please see details on the contact page.

Research Interests: Robotics, Reinforcement Learning, 3D Perception, World Models.
Current Applications: Humanoids in Personal/Service, Self-Driving Labs and Surgical/Medical robotics.

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