Personal profile
Research interests
Dr. Lei Liu is a Professor in the Division of Biostatistics at Washington University in St. Louis. He has diverse research interests in biostatistical and data science methods, including survival analysis, longitudinal data analysis, spline regression, personalized medicine, and machine learning. His research is focused on the analysis of high dimensional omics (epigenetics and microbiome) data, medical cost data, and joint models of multi-outcome data. He collaborates with clinicians in various medical fields, e.g., cancer, cardiovascular, addiction, ophthalmology, nephrology, infectious disease, asthma, and diabetes. Dr. Liu is a Fellow of the American Statistical Association. He is an associated editor of Biometrics and Statistics in Medicine, and an editorial board member of the Journal of the National Cancer Institute and Frontiers in Psychiatry. He is a standing member of NIH Biostatistical Methods and Research Design Study Section (2016-22), the only study section focusing on biostatistical methodology development. He also reviews grants frequently for other NIH study sections and other funding agencies around the world.
Mentoring
My commitment to promoting diversity and inclusion in academia is grounded in my personal experience from research and teaching. I have fruitful collaborations with underrepresented minority (URM) colleagues, resulting in over 20 joint publications, and many NIH funded grants. At Washington University in St. Louis, I am a faculty mentor of the NHLBI funded Programs to Increase Diversity among Individuals Engaged in Health-Related Research (PRIDE). Through this program I help promote the research capability of the junior URM faculty members, in particular the grant writing skills. I will continue to pursue efforts to enhance diversity, equity and inclusion
Available to Mentor:
- PhD Students
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Collaborations and top research areas from the last five years
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A Multicomponent Strategy to Increase Human Papillomavirus Vaccination Rates in Primary Care: A Cluster Randomized Clinical Trial
Wang, R., Liu, L., Dodd, S., Graham, S., Rook, S., Ericson, L., Plax, K., Barker, A., McKay, V., Silver, M., Newland, J. & King, A., Feb 26 2026, In: JAMA Network Open. 9, 2, e260049.Research output: Contribution to journal › Article › peer-review
Open Access1 Link opens in a new tab Scopus citations -
Deep Neural Network With a Smooth Monotonic Output Layer for Dynamic Risk Prediction
Zhou, Z., Deng, Y., Liu, L., Jiang, H., Peng, Y., Yang, X., Zhao, Y., Ning, H., Allen, N. B., Wilkins, J. T., Liu, K., Lloyd-Jones, D. M. & Zhao, L., Feb 2026, In: Statistics in medicine. 45, 3-5, e70401.Research output: Contribution to journal › Article › peer-review
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Investigating Multiple Causal Mechanisms with Multiple Mediators and Estimating Direct and Indirect Effects: A Joint Modeling Approach for Recurrent and Terminal Events
Niu, F., Zheng, C. & Liu, L., Jun 2026, In: Statistics in Biosciences. 18, 2, p. 319-340 22 p.Research output: Contribution to journal › Article › peer-review
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A double exponential gamma-frailty model for clustered survival data
Xie, M., Zhou, J. & Liu, L., 2025, In: Journal of Nonparametric Statistics. 37, 4, p. 772-795 24 p.Research output: Contribution to journal › Article › peer-review
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An Efficient Testing Procedure for High-Dimensional Mediators with FDR Control
Bai, X., Zheng, Y., Hou, L., Zheng, C., Liu, L. & Zhang, H., Dec 2025, In: Statistics in Biosciences. 17, 3, p. 615-629 15 p.Research output: Contribution to journal › Article › peer-review