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I am an associate professor of statistics at the University of Michigan and a (part-time) researcher at the MBZUAI Institute of Foundation Models (IFM), where I help train fully/totally open LLMs. My research leverages statistical science to make AI smarter and more reliable. Some topics of recent interest include

• AI evaluation,
• algorithmic fairness,
• transfer learning.

Before coming to Michigan, I obtained my PhD and BA in computational math from Stanford University, advised by Michael Saunders and Jonathan Taylor, and Rice University respectively. I was born in Hangzhou, but I spent my formative years in Singapore and the SF Bay Area.

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