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Emily Fox
Professor, Statistics
Professor, Computer Science
Member, Bio-X
Member, Wu Tsai Human Performance Alliance
Member, Institute for Computational and Mathematical Engineering (ICME)
Member, Wu Tsai Neurosciences Institute
Ph.D., Massachusetts Institute of Technology (MIT), Electrical Engineering and Computer Science (2009)
E.E., Massachusetts Institute of Technology (MIT), Electrical Engineering and Computer Science (2008)
M.Eng., Massachusetts Institute of Technology (MIT), Electrical Engineering and Computer Science (2005)
S.B., Massachusetts Institute of Technology (MIT), Electrical Science and Engineering (2004)
Affiliation:
Emily Fox is a Professor in the Departments of Statistics and Computer Science at Stanford University. Prior to Stanford, she was the Amazon Professor of Machine Learning in the Paul G. Allen School of Computer Science & Engineering and Department of Statistics at the University of Washington. From 2018-2021, Emily led the Health AI team at Apple, where she was a Distinguished Engineer. Before joining UW, Emily was an Assistant Professor at the Wharton School Department of Statistics at the University of Pennsylvania. She earned her doctorate from Electrical Engineering and Computer Science (EECS) at MIT where her thesis was recognized with EECS' Jin-Au Kong Outstanding Doctoral Thesis Prize and the Leonard J. Savage Award for Best Thesis in Applied Methodology.
Emily has been awarded a CZ Biohub Investigator Award, Presidential Early Career Award for Scientists and Engineers (PECASE), a Sloan Research Fellowship, ONR Young Investigator Award, and NSF CAREER Award. Her research interests are in modeling complex time series arising in health, particularly from health wearables and neuroimaging modalities.
Emily has been awarded a CZ Biohub Investigator Award, Presidential Early Career Award for Scientists and Engineers (PECASE), a Sloan Research Fellowship, ONR Young Investigator Award, and NSF CAREER Award. Her research interests are in modeling complex time series arising in health, particularly from health wearables and neuroimaging modalities.