Gen Li

Gen Li

Gen Li

Assistant Professor


722 W 168 St, Floor R6/Room 650
New York NY US 10032
Website address: Email: CV:


Dr. Gen Li is devoted to developing new statistical learning methods for analyzing high dimensional biomedical data. He focuses on analyzing complex data with heterogeneous types that are collected from multiple sources. His methodological research interests include dimension reduction, predictive modeling, association analysis, and functional data analysis. He is also interested in genetics and bioinformatics. He is a consortium member of the NIH Common Fund program Genotype-Tissue Expression (GTEx) project, and contributes to the development of statistical methods for expression quantitative trait loci analysis in multiple tissues. He also has research interests in scientific domains including melanoma, microbiome, and urology research.



PhD, 2015, University of North Carolina at Chapel Hill
BS, 2010, Beijing Normal University

Mailman Affiliations

Faculty, Department of Biostatistics

Other Affiliations

Member, American Statistical Association
Member, Institute of Mathematical Statistics
Member, International Biometric Society, Eastern North American Region
Member, International Chinese Statistical Association

Honors & Awards

Calderone Junior Faculty Award, 2016
ENAR Distinguished Student Paper Award, 2014
IMS Travel Award, 2014
Cambanis-Hoeffding-Nicholson Award (UNC), 2011

Areas of Expertise

Big Data, Bioinformatics, Predictive Modeling/Machine Learning, Genetics, Statistical Genetics

Select Publications

Gen Li, Sungkyu Jung. "Incorporating covariates into integrated factor analysis of multi-view data." Biometics, to appear.
Xiaoyu Song, Gen Li, Zhenwei Zhou, Xianling Wang, Iuliana Ionita-Laza, Ying Wei. "QRank: A novel quantile regression tool for eQTL discovery." Bioinformatics, to appear.
Yao Shen, Milda Stanislauskas, Gen Li, Deyou Zheng, Liang Liu. "Epigenetic and genetic dissections of UV-induced global gene dysregulation in skin cells through integrative omics analyses." Scientific Reports, 7: 42646, 2017.
Gen Li, Dan Yang, Andrew B. Nobel, Haipeng Shen. "Supervised singular value decomposition and its asymptotic properties." Journal of Multivariate Analysis, 146: 7-17, 2016.
Gen Li, Haipeng Shen, Jianhua Z. Huang. "Supervised sparse and functional principal component analysis." Journal of Computational and Graphical Statistics, 25(3): 859-878, 2016.
The GTEx Consortium. "The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans." Science, 348(6235): 648-660, 2015.

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