He is developing methods for integrating and analyzing heterogeneous data types, including next-generation genome and transcriptome sequencing, metabolomics, proteomics, and electronic medical records. He and members of his laboratory develop algorithms and methods based on rigorous computational and mathematical approaches that can be used to account for the lack of controls within large, heterogenous data sets. The goals of his research are to understand basic biology, and ultimately to use this knowledge to improve human health.