Molei Liu

Welcome to my personal page!

Research Interests

I am mainly interested in developing novel analytical tools to address statistical challenges (including high-dimensionality, paucity of accurate labels, heterogeneity, privacy constraints, etc) in analyzing large-scale electronic health record (EHR) and biobank data. Relevant statistical research areas include: high-dimensional statistics, semiparametric inference, federated learning, data-fusing, semi-supervised learning, transfer learning, model-X inference, and selective inference. My developed methods have been applied for EHR phenotyping and model evaluation, multi-source data aggregation, genetic risk modeling, phenotype-genotype association studies, clinical knowledge extraction, etc.

Experiences

I am now a tenure-track Assistant Professor (2022-present) at Department of Biostatistics, Columbia University Mailman School of Public Health.

I obtained my Ph.D. (2017-2022) degree at Department of Biostatistics, Harvard Chan School of Public Health, advised by Tianxi Cai. My thesis advisor committee also includes Lucas Janson and Junwei Lu.

Prior to PhD, I did my undergraduate (2013-2017) in School of Mathematical Sciences, Peking University (advised by Xiaohua Zhou, Hao Ge and Minping Qian) and did summar intern (2016) at Hongyu Zhao's group, Department of Biostatistics, Yale school of Public Health.