Xiao Wu is a Ph.D. candidate in the Department of Biostatistics at Harvard University, where he is advised by Dr. Francesca Dominici and Dr. Danielle Braun. His research interests lie in developing causal inference methods to address methodological needs in environmental health and public policy evaluation using large-scale healthcare databases. His dissertation work focuses on developing robust and interpretable causal inference methods to handle error-prone, continuous, and time-series exposures. He is also working on collaborative projects to design Bayesian clinical trials, meta-analysis, and real-world evidence studies.
His research has been published in prestigious scientific venues such as Science Advances, the Lancet Planetary Health, and the Annals of Applied Statistics, and it has attracted the attention of international journalism, including at the New York Times, the Guardian, National Geographic, USA Today, and Scientific American among others.
Ph.D. in Biostatistics, 2021 (Expected)
M.S. in Biostatistics, 2017
Harvard T.H. Chan School of Public Health
LL.B. in Laws, B.S. in Mathematics, 2015