Fang Han

Fang Han is an Associate Professor in the Department of Statistics at the University of Washington and an Adjunct Professor in Economics. He is also an Affiliated Investigator at Fred Hutchinson Cancer Research Center. His research focuses on rank-based and graph-based methods, statistical optimal transport, and nonparametric/semiparametric regression.

• Education:
  • Ph.D. in Biostatistics, Johns Hopkins University (2015) - supported by Google Ph.D. Fellowship
  • M.S. in Biostatistics, University of Minnesota
  • B.S. in Mathematics, Peking University

Research interests span rank correlation, causal inference, nonparametric regression, high-dimensional statistics, and random matrix theory. His recent work includes adaptations of Chatterjee's correlation to manifold data and rigorous analysis of matching estimators' variance.

Scientific awards include

• Bernoulli Society New Researcher Award (2021)
• Google Ph.D. Fellowship (2013-2015)
• Margaret Merrell Award (2015)
• National Science Review 2015 Best Paper (2016)

Teaching includes courses like Advanced Theory of Statistical Inference, Time Series Analysis, and Foundations of Machine Learning. He serves as Associate Editor for Bernoulli and editorial board member for Dependence Modeling.