I am a theoretical neuroscientist and research fellow at the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University.
Neural circuits are characterized by their large scale, nonlinear dynamics, complex recurrent interactions, and connections that change across multiple timescales. I use tools from statistical physics and machine learning to understand how these features enable computation and learning.
I earned my Ph.D. in Neurobiology and Behavior from Columbia University in the Center for Theoretical Neuroscience, where I was primarily advised by Larry Abbott and worked closely with Ashok Litwin-Kumar and Haim Sompolinsky. Before that, I studied physics and computer science at UC Berkeley.
My publications are listed below, or see Google Scholar. My CV is here.
Outside of science, I see a lot of Broadway.
Feb. 6, 2025