Brielin Brown is a postdoctoral research fellow at the Data Science Institute with a joint affiliation with the New York Genome Center. His research lies at the intersection of machine learning and genomics. He is broadly interested in understanding how genetics and environmental factors change people‚Äôs cellular functions and lead to disease. To this end, he develops machine learning algorithms for modeling and inference in large-scale genomic studies. Before coming to Columbia, he completed a Ph.D. in computer science from the University of California, Berkeley, and worked as a computational biologist at Verily Life Sciences. As a Ph.D. student, he was supported by a National Science Foundation fellowship and a Chancellor’s Fellowship for graduate study. He completed his undergraduate studies at the University of Virginia, earning a B.S. in physics and a B.A. in computer science. In his spare time, he enjoys techno music and is an avid surfer.