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.
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, Data Science, Predictive Modeling/Machine Learning, Genetics, Statistical Genetics
Gen Li, Irina Gaynanova. "A general framework for association analysis of heterogeneous data." Annals of Applied Statistics, accepted, 2017+.
Gen Li, Andrey A. Shabalin, Ivan Rusyn, Fred A. Wright, Andrew B. Nobel. "An empirical Bayes approach for multiple tissue eQTL analysis." Biostatistics, accepted, 2017+.
Gen Li, Jianhua Z. Huang, Haipeng Shen. "To wait or not to wait: Two-way functional hazards model for understanding waiting in call centers." Journal of the American Statistical Association, accepted, 2017+.
Gen Li, Sungkyu Jung. "Incorporating covariates into integrated factor analysis of multi-view data." Biometics, 73(4): 1433-1442, 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.
Xiaoyu Song, Gen Li, Zhenwei Zhou, Xianling Wang, Iuliana Ionita-Laza, Ying Wei. "QRank: A novel quantile regression tool for eQTL discovery." Bioinformatics, 33(14): 2123-2130, 2017.
GTEx Consortium. "Genetic effects on gene expression across human tissues." Nature, 550(7675): 204-213, 2017.
The GTEx Consortium. "The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans." Science, 348(6235): 648-660, 2015.