I am an assistant professor of Statistics at the University of Michigan.

Previously, I was a postdoctoral researcher with Professor Michael Jordan at the University of California, Berkeley. I completed Ph.D. in Statistics at Columbia University in 2020, advised by Professor David Blei, and B.Sc. in mathematics and computer science at the Hong Kong University of Science and Technology in 2014.

I work in the fields of machine learning, causal inference, and Bayesian statistics. See my CV and publications.

My research interests include

• Probabilistic generative modeling/Bayesian statistics: Probabilistic approaches to large language models and diffusion models, statistical and computational theory of variational Bayes, robust Bayesian inference
• Causal machine learning/Causal inference: Causal representation learning, causal inference for language models, statistical inference and computational approaches for causal inference
• Applications: Recommender systems, computational biology, electronic health records, materials discovery, human-AI interactions

During the semester, I hold weekly office hours in person and over zoom.

Postdoc position available: I have an opening for a postdoc to join my research group to work on causal machine learning and/or probabilistic generative modeling.