Emily Fox

SVP of AI and Machine Learning


Los Angeles


S.B., M.Eng., E.E., and Ph.D. from the Department of Electrical Engineering and Computer Science at MIT

Emily Fox, Ph.D., serves as our senior vice president of AI/machine learning. Emily is a professor in the Department of Statistics and Department of Computer Science at Stanford University, where she has made groundbreaking contributions in the application of machine learning in healthcare, with her pioneering work directly translating into patient impact.  

Prior to joining Stanford, Emily established, grew, and led the Health AI team at Apple, where she was a Distinguished Engineer. At Apple, her team collaborated cross-functionally on health and wellness projects leveraging Apple’s ecosystem of devices and software, as well as studies with partners including Aetna, Johnson & Johnson, Eli Lilly, and the Seattle Flu Study. She also served as 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. Her academic research has focused on discovering interpretable latent structure from complex, high-dimensional scientific and clinical datasets, with an emphasis on data arising in genomics and neuroscience, and on machine learning for healthcare applications, including the use of wearable devices and other in-the-wild sensing modalities. 

Her work has been recognized with her selection as a CZ Biohub – San Francisco Investigator (2022-2027) and serving as the NeurIPS Program co-chair in 2019. She has also been awarded a Presidential Early Career Award for Scientists and Engineers (PECASE), Sloan Research Fellowship, ONR Young Investigator award, and NSF CAREER award. Her Ph.D. thesis was recognized with the Leonard J. Savage Thesis Award in Applied Methodology and MIT EECS Jin-Au Kong Outstanding Doctoral Thesis Prize.