Lerrel Pinto is a researcher at New York University specializing in robotics, with a focus on improving robot dexterity, robustness, and generalization. He has contributed to advancements in visual imitation techniques, leveraging visual representations and k-NN regression for both offline and real-world robotic tasks. Pinto actively shares his research outputs, including papers and code, underscoring his expertise in robotics and artificial intelligence.

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