In this episode, I talk with Lerrel Pinto, Assistant Professor at NYU and one of the most cited researchers in robotics today:

His work spans everything from self-supervised learning to robot dexterity, and he's on a mission to make robots generalize the way humans do.

We talk about growing up in India, building his own education at IIT, and what led him to Carnegie Mellon, Berkeley, and now New York. Lerrel explains how his lab at NYU, GRAIL, tackles robot learning at scale (from representation learning to reinforcement learning) and why open-source, affordable robots are core to his approach.

He also shares what it’s like launching his new stealth-mode startup, Assured Robot Intelligence (ARI), while running one of the top research labs in the country. We talk about how his teaching, mentoring, and outreach are shaping the next generation of roboticists.