Dr. Emily Fox

Professor

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Biography

Emily Fox is a Professor in the Departments of Statistics and Computer Science at Stanford University. Before joining Stanford, she served as a Professor of Machine Learning at the Paul G. Allen School of Computer Science & Engineering and the Department of Statistics at the University of Washington from 2018 to 2021. Earlier in her career, she was a Distinguished Engineer leading the Health AI team at Apple. Additionally, she held the position of Assistant Professor at the Wharton School in the Department of Statistics at the University of Pennsylvania. Emily earned her Ph.D. in Electrical Engineering and Computer Science from MIT in 2009, receiving the Jin-Au Kong Outstanding Doctoral Thesis Prize for her work. She is recognized for her contributions to applied methodology and has received multiple prestigious awards, including the CZ Biohub Investigator Award, the Presidential Early Career Award for Scientists and Engineers (PECASE), a Sloan Research Fellowship, and the ONR Young Investigator Award. Her research interests focus on modeling complex time series data arising from health applications, particularly related to health wearables and neuroimaging modalities.

Research Interests

Awards

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CZ Biohub Investigator Award

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Presidential Early Career Award for Scientists and Engineers (PECASE)

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Sloan Research Fellowship

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ONR Young Investigator Award

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NSF CAREER Award

Requirements for Stanford University

Doctorate Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Listening
Required:26
Reading
Required:26
Writing
Required:26
Speaking
Required:26
Total
Required:100
GRE General
Verbal
Required:160
Quantitative
Required:165
Analytical Writing
Required:4.5
Overall
Required:4.5
Prerequisites
Bachelor degree from an accredited institution Strong background in mathematics and programming
Application Checklist
  • Statement of Purpose
  • Three letters of recommendation
  • Official transcripts
  • Resume/CV
Specialization Notes

The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.