His research interests include numerical optimization problems, particularly those arising from statistical analysis of high-dimensional data such as large-scale genomic data. He has developed penalization methods for association screening of genome-wide association (GWAS) and next generation sequencing (NGS) data, and a nonlinear dimension reduction approach for genotype aggregation and association mapping. Currently he is working on genome-wide QTL association mapping based on family designs, genotype imputation, transcriptomics data analysis based on RNA-seq technology, and statistical methods for analyzing microbiome data.