Anastasios Angelopoulos
Ph.D. student in Electrical Engineering and Computer Science
at the University of California, Berkeley
Student of Michael I. Jordan
and of Jitendra Malik
Research interests
Building out Distribution-Free Uncertainty Quantification, motivated by applications to medicine and computational imaging.
Recent News
October, 2022 I was lucky to collaborate with Bat-Sheva Einbinder, who showed that conformal prediction is robust to certain types of label noise in her new paper. Take a look!
September, 2022 We made a major update to the Gentle Intro. Check out the new codebase here!
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).
