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Talk title:

Using Embodied Agents to Reverse-Engineer Natural Intelligence

Date: Friday, December 5, 2025

Time: 3-4 p.m.

Location: MY580 and

Abstract:

Modern AI faces (at least!) two challenges: (1) building agents capable of autonomy and life-long learning, and (2) embodying them to perform these tasks in the real-world. In this talk, I will discuss our approach to these questions, and show that they also are tightly intertwined with reverse-engineering brains across multiple species, from rodents to non-human and human primates. In other words, by setting the general capabilities of humans and animals as concrete engineering targets, we show that building more capable autonomous agents both advances AI and deepens our computational understanding of large-scale neural populations being collected today (on the order of hundreds of thousands of neurons), thereby forming a tight two-way loop between neuroscience and AI.

Bio:

I’m an Assistant Professor at , a core faculty member of the , and hold a courtesy appointment in the .

My lab, the , works at the intersection of neuroscience & AI to reverse-engineer animal intelligence and build the next generation of autonomous agents, responsibly and safely.

Previously, I was an  Postdoctoral Fellow at MIT, primarily working with  and . I completed my PhD ( & ) in the , co-advised by  and . Before that, I completed my Master’s in Computer Science (AI Specialization), as well as my undergraduate major in Mathematics (with a secondary degree in ), at Stanford University. During that time, I did work in theoretical computer science and other areas of math. My  is .