I am an assistant professor at Cornell University in the Computer Science Department.
Before Cornell, I was a research fellow in the Center for Computational Mathematics at the Flatiron Institute. I completed a Ph.D. in Computer Science from Princeton University, where I was advised by Ryan Adams and Barbara Engelhardt. I was supported in part by a Google PhD Fellowship in Machine Learning. I received an A.B. in Computer Science and Statistics from Harvard University, an M.S. in Statistics from the University of Chicago, and an M.A. in Computer Science from Princeton University.
Research interests:
• approximate inference [SBI, variational inference, MCMC]
• generative models under misspecification [mixture modeling, graphs]
• ML for science [e.g., material science, genomics]