About
I am a postdoctoral researcher in the Department of Computer Science at Princeton University, where I work with Tom Griffiths. I earned my Ph.D. from the Department of Computer Science at the University of Toronto, where my advisor was Richard Zemel.
I work on the intersection of deep learning and probabilistic modeling to build adaptable and reliable machine learning algorithms. My current research interests include:
1. Building learning algorithms that generalize better with limited data.
2. Designing inference algorithms for quantifying the reliability of AI models.
Research keywords: deep learning, metalearning, continual learning, Bayesian inference, uncertainty quantification, nonparametric statistics.
I am on the academic job market for 2024-2025!
