(734) 764-5450

Applications:
Genomics
Methodologies:
Algorithms, Computational Tools for Data Science, Data Mining, Heterogeneous Data Integration, High-Dimensional Data Analysis, Machine Learning, Network Analysis, Predictive Modeling, Sparse Data Analysis, Statistical Modeling, Statistics, Tensor Analysis
Relevant Projects:

NIH


Gen Li

Assistant Professor

Department of Biostatistics

Dr. Gen Li is an Assistant Professor in the Department of Biostatistics. He 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.

Novel tree-guided regularization methods can identify important microbial features at different taxonomic ranks that are predictive of the clinical outcome.