Gen Li, Ph.D.
John G. Searle Associate Professor of Biostatistics
Dr. Gen Li is an Assistant Professor in the Department of Biostatistics. Before joining the University of Michigan in 2020, he was an Assistant Professor in the Department of Biostatistics at Columbia University from 2015 to 2020. Dr. Li is devoted to developing new statistical methods for analyzing complex biomedical data, including multi-way tensor array data, multi-view data, and compositional data. His methodological research interests include dimension reduction, predictive modeling, association analysis, and functional data analysis. He also has research interests in scientific domains including microbiome and genomics.
- PhD, Statistics and Operations Research, University of North Carolina at Chapel Hill, 2015
- BS, Statistics, Beijing Normal University, 2010
Microbiome data analysis; tensor array methods; low-rank models; multi-view data integration; high-dimensional data analysis.
- The GTEx Consortium (2015). The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science, 348(6235): 648-660.
- Gen Li, Dan Yang, Andrew B. Nobel, Haipeng Shen (2016). Supervised singular value decomposition and its asymptotic properties. Journal of Multivariate Analysis, 146: 7-17.
- Gen Li, Sungkyu Jung (2017). Incorporating covariates into integrated factor analysis for multi-view data. Biometrics, 73(4): 1433-1442.
- GTEx Consortium (2017). Genetic effects on gene expression across human tissues. Nature, 550(7675): 204-213.
- Eric F. Lock, Gen Li (2018). Supervised multiway factorization. Electronic Journal of Statistics, 12(1): 1150-1180.
- Gen Li, Andrey A. Shabalin, Ivan Rusyn, Fred A. Wright, Andrew B. Nobel (2018). An empirical Bayes approach for multiple tissue eQTL analysis. Biostatistics, 19(3): 391-406.
- Gen Li, Irina Gaynanova (2018). A general framework for association analysis of heterogeneous data. The Annals of Applied Statistics, 12(3): 1700-1726.
- Gen Li, Jianhua Z. Huang, Haipeng Shen (2018). To wait or not to wait: Two-way functional hazards model for understanding waiting in call centers. Journal of the American Statistical Association, 113(524): 1503-1514.
- Gen Li, Xiaokang Liu, Kun Chen (2019). Integrative multi-view regression: bridging group-sparse and low-rank models. Biometrics, 75(2): 593-602.
- Irina Gaynanova, Gen Li (2019). Structural learning and integrative decomposition of multi-view data. Biometrics, 75(4): 1121-1132.