About
I am a postdoc in the Dept. of Computer Science at Princeton University, where I work with Tom Griffiths. I earned my Ph.D. in computer science at U of Toronto, where my advisor was Richard Zemel. Previously, I completed my bachelor's degree in biomedical engineering at Yale.
I work on building trustworthy deep learning algorithms through the perspective of probabilistic modeling. My current research interests include:
1. Robustness. Designing learning algorithms that are robust to new environments and changes over time, with a particular focus on meta-learning and Bayesian filtering.
2. Reliability. Quantifying the reliability of black box models, with an emphasis on distribution-free and nonparametric methods.
3. Transparency. Developing Bayesian inference algorithms to better understand representations and behavior of AI models.
I am on the academic job market for 2024-2025!
