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Xinran Li is an Assistant Professor in the Department of Statistics and the College at the University of Chicago. His research primarily focuses on developing novel methodologies for causal inference. He specializes in randomization-based inference of causal effects, sensitivity analysis in observational studies, and experimental design with a particular emphasis on rerandomization. Furthermore, he employs Bayesian inference methodologies in his work. Xinran is passionate about exploring new avenues to apply advanced methodologies in the social and biomedical sciences, reflecting his commitment to innovation in statistical applications.
Department of Philosophy