Summary
Hufeng Zhou is an interdisciplinary computational biologist and instructor with nine years of research experience bridging statistical genetics, machine learning, and next-generation sequencing to dissect host–pathogen interactions and viral oncology. With a Ph.D. from the National University of Singapore and current roles at Harvard Medical School and Brigham and Women’s Hospital, he leads large-scale WGS and epigenomic analyses—applying ChIP-seq, Hi-C, ChIA-PET, RNA-seq and related assays—to map regulatory architecture in EBV-associated cancers. His work combines rare-variant discovery in massive cohorts (TOPMed, UK Biobank, All of Us) with functional annotation of noncoding variants and cross-species protein–protein interaction modeling to reveal mechanistic links to infection, immunity, and cardiometabolic traits. Hufeng also builds scalable genomics resources (e.g., FAVOR-style tools and databases) and curates pathway and metagenomic data to enable systems-level inference, reflecting a rare blend of computational rigor and translational focus. Notably, his background includes hands-on assay development for viral super-enhancer discovery, underscoring an ability to move from wet-lab designs to population-scale computational insight.
8 years of coding experience
Doctor of Philosophy (Ph.D.), Computational Biology, 4.82/5.00, Doctor of Philosophy (Ph.D.), Computational Biology, 4.82/5.00 at National University of Singapore