His research is focused on developing statistical models and machine learning algorithms to infer large-scale context-dependent gene regulatory networks and leveraging the network predictions for human disease analysis. Major research topics in Dr. Wang's group include inference of long-range enhancer-gene networks and associated 3D chromatin structure, delineation of hierarchical regulatory grammar of gene expression, genome-wide regulatory element prediction based on high-dimensional epigenetic features, efficient signal processing for high-throughput biological dataset, and functional annotation of non-coding genetic variants in diverse human diseases.