I am an assistant professor in the Computer and Information Science department at the University of Pennsylvania. I do research in machine learning, with a focus scalable probabilistic machine learning methods and Bayesian machine learning. Recently, I've also been interested in how machine learning techniques can be applied to large-scale, high dimensional optimization problems in the natural sciences. In 2022, I received an NSF CAREER award funding work on these kinds of optimization problems.
Before I joined Penn, I was a research scientist at Uber AI Labs. Before this, I was a postdoctoral associate in Operations Research and Information Engineering at Cornell University. I received my Ph.D. in Computer Science from Cornell University, where I was advised by Kilian Weinberger .
Discovering Many Diverse Solutions with Bayesian Optimization [Paper] Natalie Maus, Kaiwen Wu, David Eriksson, Jacob Gardner (Preprint.)
Virtual Seminar Series on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems | An online seminar series to
Yurong You | Homepage
Geoff Pleiss
Kyurae Kim
Kyurae Kim
Xinran Zhu | Homepage
Ke Alexander Wang