Ph.D. student in Electrical Engineering and Computer Science

at the University of California, Berkeley

Student of Michael I. Jordan
and of Jitendra Malik

Building out Distribution-Free Uncertainty Quantification, motivated by applications to medicine and computational imaging.

*August, 2022* Check out our paper, Conformal Risk Control. Shockingly, conformal prediction can be used to bound risk functions far beyond coverage. This is a short and useful read (the theory section is 2 pages).

*July, 2022* Thanks to everyone who came to the 2022 ICML Workshop on Distribution-free Uncertainty Quantification on July 23, 2022. It was a blast!

*July, 2022* I'm a bit late to shout out the following papers, so I'll do it all at once. NEW: Linear Revolution Invariance: Modeling and Deblurring Spatially-Varying Imaging Systems, Recommendation Systems with Distribution-Free Reliability Guarantees, Improving Trustworthiness of AI Disease Severity Rating in Medical Imaging with Ordinal Conformal Prediction Sets, Semantic uncertainty intervals for disentangled latent spaces. Also, Im2Im-Uq was accepted in ICML'22!