Department of Statistics and the College
Frederic Koehler’s research interest lies in fundamental problems at the intersection of algorithms, statistics, and learning. His recent research has focused on understanding the interplay between memorization and generalization to unseen examples, analyzing trade-offs between computational and statistical efficiency, and designing algorithms for sampling from complex, high-dimensional distributions.
His research has been published or presented in such venues as Advances in Neural Information Processing Systems, Probability Theory and Related Fields, the Symposium on Theory of Computing, International Conference on Research in Computational Molecular Biology, and Conference on Learning Theory.
Koehler earned a BA in mathematics from Princeton University and a PhD in mathematics and statistics from the Massachusetts Institute of Technology. Most recently, he was the Rajeev Motwani postdoctoral fellow in the Department of Computer Science at Stanford University. He will join the University of Chicago faculty on January 1, 2024.