Julia Salzman is an Associate Professor in the Department of Biomedical Data Science, Biochemistry and Statistics (by Courtesy). She received her BA in Mathematics from Princeton University Magna Cum Laude and PhD from Stanford University in the Department of Statistics supervised by Persi Diaconis. After a year on the faculty in the Department of Statistics at Columbia University, she returned to Stanford to study genomics. She joined the Stanford faculty in 2013. As a postdoctoral scholar in Patrick Brown’s lab, 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. Salzman’s research is funded by the NIH and NSF, and has been recognized by awards including an Alfred P. Sloan Fellowship in Computational Biology; a McCormick-Gabilan Fellowship, an NSF CAREER Award. Her research spans the interface of statistical methodology and genomics aiming to use data driven experiments to uncover organizing principles of biological regulation.

The combination of digital biological data, statistical formalism and computational science promise to significantly advance many areas of biology ranging from organizing principles of cellular development to unraveling mechanisms of microbial growth and communication to biomarker applications. Salzman's group develops a variety of statistical algorithms aimed at making inroads into these fundamental questions and has historically focused on regulated RNA processing.