Research

I work on the science of deep learning. I've had the privilege of learning to do research from Sam Gershman and Aditi Raghunathan. This is some of the work I published as an undergraduate.

I'm interested in understanding what systems centered around foundation models will look like in 5 years, and how they will touch our lives in unthinkable ways. Reasoning models and computer use/software agents are two nascent examples, but I think and hope that AI systems will play a more transformative role in our day to day lives than mere automation. My research style usually involves studying these models in a scientific way, running experiments across the stack: from pretraining to evals and beyond.

My path into deep learning was a meandering one. I was taken in by multiple research communities broadly studying artificial intelligence when I was an undergraduate. Two prominent ones were physicists studying the brain -- who think of neural networks as freshly discovered platonic objects, pure and unsullied -- and computer systems people who like to hack and think of neural networks as graphs of differentiable tensor operations nested inside GPU cores, where the key goal is maximizing arithmetic intensity. I am fortunate to have been a part of and be mentored by folks in both communities.