Jake A. Soloff

I am an assistant professor of statistics at the University of Michigan. My research examines the theoretical and philosophical foundations of statistical machine learning, aiming to develop methods that are both principled and broadly applicable.

Previously, I received my PhD in statistics from UC Berkeley in 2022, advised by Aditya Guntuboyina and Michael I. Jordan, and completed a postdoc at the University of Chicago with Rina Foygel Barber and Rebecca Willett.