Speaker

Julia Salzman is an Associate Professor in the Department of Biomedical Data Science, Biochemistry and Statistics (by Courtesy). She received her A.B. in Mathematics from Princeton University Magna Cum Laude and Ph.D. from Stanford University in the Department of Statistics supervised by Dr. Persi Diaconis. As a postdoctoral scholar in Dr. Patrick Brown’s lab, Dr. Salzman developed statistical algorithms that led to the discovery of a ubiquitous expression of circular RNA missed by other computational and experimental approaches for decades. Her research spans the interface of statistical methodology and genomics aiming to use data driven experiments to uncover organizing principles of biological regulation, historically focused on RNA processing. Recently her group has introduced a new approach to sequencing analysis called NOMAD that performs inference on raw sequencing data, bypassing genome alignment. This approach is providing new insights into RNA regulation including RNA editing and splicing among many other applications.

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