Dr. Chen received his B.E. from Tsinghua University (Beijing), Ph.D. from University of Illinois at Urbana-Champaign, and postdoctoral training from University of California at San Diego. From 2005 to 2011, he worked for Washington University School of Medicine in St. Louis as a senior scientist and a research faculty. Having a background in machine learning, statistical signal processing, and cancer genomics, his primary goal is to develop computational tools to analyze and interpret human genomics and clinical data towards the realization of genomic medicine. Dr. Chen has designed, developed, and co-developed a set of computational tools such as BreakDancer, VarScan, and Monovar that have been widely applied to characterize individual and population genomics in various large-scale next-generation sequencing projects such as those in the Cancer Genome Atlas (TCGA) and the 1000 Genomes Project. He is particularly interested in comprehensively and accurately constructing the genomes and the transcriptomes of various cancer cell populations towards understanding the heterogeneity and the evolution of cancer as a consequence of genetics and environment. He is also interested in developing integrative (AI-based) approaches to identify biomarkers that are useful for diagnosis and prognosis. More information about his research group is available here.