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I am an associate professor of statistics at the University of Michigan. 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