Nathan Sheffield

Nathan Sheffield is an Associate Professor of Genome Sciences in the School of Medicine, with additional appointments in Biomedical Engineering, Biochemistry and Molecular Genetics, and at the School of Data Science. His research interests span computational biology, bioinformatics, biomedical data sciences, machine learning, epigenomics, gene regulation, chromatin, and high-performance computing.

The Sheffield Lab applies computational and data science methods to explore fundamental questions in genome biology. By leveraging cutting-edge techniques from representational learning and natural language processing, they aim to decode the language of DNA, uncovering how genes are regulated and expressed. They study how diseases like cancer hijack normal regulatory programs, using computational methods to uncover mechanisms that drive disease.

Sheffield earned his B.S. in Bioinformatics from Brigham Young University, and then his Ph.D. in Computational Biology and Bioinformatics from Duke University, where his  research focused on computational epigenomics. He then focused on human disease as a Postdoctoral Fellow in Christoph Bock’s Lab at the Center for Molecular Medicine in Vienna and Howard Chang's lab at Stanford University. In 2016, he established his independent lab at UVA, where he continues to push the boundaries of computational biology research. In 2024, he became the founding Director of Graduate Studies for UVA PhD program in Computational Biology. As a leader in computational biology, Sheffield is committed to training the next generation of scientists and advancing genomic research to improve human health.