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I am an associate professor of statistics at the University of Michigan, and I direct the data science master’s program. My research leverages statistical science to make AI more safe and reliable in the real world. Some topics of recent interest include

• AI evaluation & safety,
• algorithmic fairness,
• learning under distribution shifts.

Before coming to Michigan, I obtained my PhD in computational mathematics from Stanford University, where I worked with Michael Saunders and Jonathan Taylor, and my BA (also in computational math) from Rice University.

I have learned a lot in my life. Unfortunately, most of it is about technicalities. – JR