BIO

I study how the human brain learns rich internal models of the world for efficient planning and decision making. I also build artificial agents that learn and plan in human-like ways. My research connects multiple disciplines, including neuroscience, psychology, machine learning, robotics, and cognitive science.

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I received my PhD from the Department of Neurobiology at Harvard University where I worked with Samuel Gershman and Naoshige Uchida on building and evaluating computational models of learning and decision making in humans and rodents. I am still pursuing this work as a Harvard affiliate while also building neurally-inspired planners for self-driving cars at Motional AD.

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Outside of lab, I enjoy biking, surfing, and the occasional ski trip.