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Jingshu Wang is an Assistant Professor in the Department of Statistics at the University of Chicago. His research primarily focuses on developing statistical methods and machine learning tools that facilitate advancements in cutting-edge biotechnologies and address complex genetic problems. He is currently engaged in projects related to single-cell multi-omics and Mendelian Randomization, where he aims to devise general statistical methods and theories for the combination of multiple p-values to enhance replicability and statistical power. His work also involves causal inference within factor models, addressing new challenges that arise in the fields of genetics and public health. Jingshu's contributions include innovative approaches that aim to improve the analysis and interpretation of data in these rapidly evolving areas.
Department of Philosophy