I am an assistant professor in the statistics department at the University of Michigan. My research is driven by statistical and computational challenges in machine learning. Some topics of recent interest are
- algorithmic fairness,
- distributed/federated learning,
- geometric algorithms for machine learning.
More broadly, I am interested in the mathematical foundations of data science. I obtained my PhD from Stanford University, where I worked with Michael Saunders and Jonathan Taylor, and my bachelor’s degree from Rice University.
I have learned a lot in my life. Unfortunately, most of it is about technicalities. – JR