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Animesh Garg is an AI Researcher and Early Career Professor at Georgia Institute of Technology, notably in the School of Interactive Computing. His expertise lies in building algorithmic foundations for generalizable autonomy in robotics, enabling systems to acquire skills that allow seamless and collaborative interactions with humans in novel environments. His research group focuses on understanding structured inductive biases and causal decision-making, with particular emphasis on multi-modal object-centric spatiotemporal event representations, self-supervised pre-training, reinforcement learning, and skill learning. Animesh has held research leadership roles at Nvidia and Apptronik, and has courtesy appointments at the University of Toronto and the Vector Institute. He is actively engaged in the robotics community, having been invited as a speaker at various prestigious conferences such as ICRA and ICLR.
Georgia Institute of Technology • Atlanta, GA
Assisting in teaching and conducting research in computer science.
Apptronik •
Led scientific research and development efforts.
Nvidia Research •
Conducted advanced research in AI and robotics.
Stanford University •
Worked on AI and robotics research.
Department of Computer Science: GRE scores are optional for Fall 2026.