Statistical Methodology · Machine Learning · Biomedical Data Science
Molei Liu 刘默雷
Researcher & Assistant Professor (Tenure Track), Peking University
I develop statistical learning methods that remain reliable across heterogeneous populations, data sources, and imperfect models, with particular interests in transfer learning, semi-supervised learning, model-X inference, and biomedical data science.
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Research
A methods-driven program motivated by modern biomedical data.
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Methodological Work
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Interdisciplinary Collaborations
Selected collaborative work connecting statistical methodology with genetics, EHRs, clinical research, and population health.
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Selective Preprints & Manuscripts
Recent manuscripts under revision or in submission.
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Research Group
Postdoctoral fellows, Ph.D. students, and master's students.
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About
Academic appointments and training.
My research lies at the intersection of statistical theory, machine learning, and biomedical data science.
A central goal is to develop reliable and efficient learning methods when populations differ, labels are limited, data are distributed across institutions, or working models are misspecified.
CONTACT
Interested in collaboration?
I welcome collaborations on methodological statistics, machine learning, EHRs, biobanks, genetics, and clinical research.
moleiliu@bjmu.edu.cn