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Emily Fox is a Professor of Statistics and Computer Science at Stanford University. Previously, she served as a Professor of Machine Learning at the Paul G. Allen School of Computer Science & Engineering and was part of the Department of Statistics at the University of Washington from 2018 to 2021. Before joining UW, she was an Assistant Professor at the Wharton School, University of Pennsylvania, also in the Department of Statistics. Emily earned her Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT), where her thesis was awarded the Jin-Au Kong Outstanding Doctoral Thesis Prize and the Leonard J. Savage Award for Applied Methodology. Her research focuses on modeling complex time series data arising from health, particularly in health wearables and neuroimaging modalities. She has received several prestigious awards, including the CZ Biohub Investigator Award in 2022 and the Presidential Early Career Award for Scientists and Engineers from the National Science Foundation in 2017. Emily has published extensively, contributing significant advancements in health-related data analysis and methodology.
The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.