About
I am a postdoctoral researcher in the Department of Computer Science at Princeton University, where I work with Tom Griffiths. I received my Ph.D. from the Department of Computer Science at the University of Toronto and the Vector Institute, where my advisor was Richard Zemel. Prior to my Ph.D., I received my M.Sc. in Computer Science from the same department and my B.Sc. in Biomedical Engineering from Yale University.
I am broadly interested in the intersection between deep learning and Bayesian inference. In my research, I use insights from Bayesian inference to design deep neural networks that are resilient and reliable, even in new environments.
Research interests: metalearning, hierarchical Bayesian models, continual learning, Bayesian filtering, nonparametric statistics, uncertainty quantification, distribution-free inference.
I am on the academic job market for 2024-2025!