Research
Scalable statistical methods for complex traits in large-scale biological data.
My research focuses on statistical genomics and the development of scalable methods for analyzing complex traits in large-scale biological data. My overall goal is to develop broadly useful statistical tools that advance biomedical research, precision health, and agricultural improvement.
Genome-wide association studies
Efficient methods for GWAS, including multi-trait analysis, longitudinal analysis, gene–environment interaction analysis, epistatic interaction analysis, and genetic subtype identification.
Gene–environment interactions
Powering genome-wide detection of genotype–environment interactions at biobank scale (fastGxE).
Integrative multi-omics analysis
Integrating whole-genome sequencing, transcriptomics, proteomics, methylomics, and functional genomics data to identify functional genes and biological mechanisms.
Quantitative genetics & genomic selection
Quantitative genetics, genetic evaluation, and genomic selection in livestock, particularly dairy cattle and pigs.