Stanford University
Showing 1,621-1,640 of 6,214 Results
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Emily Fox
Professor of Statistics and of Computer Science
BioEmily 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. -
John Fox
Adjunct Professor
Current Research and Scholarly InterestsStanford University Research areas center on optimal control methods to improve energy
efficiency and resource allocation in plug-in hybrid vehicles. Stanford graduate courses
taught in laboratory techniques and electronic instrumentation. Undergraduate course
"Energy Choices for the 21st Century" -
Michael Frank
Benjamin Scott Crocker Professor of Human Biology and Professor, by courtesy, of Linguistics
Current Research and Scholarly InterestsHow do we learn to communicate using language? I study children's language learning and how it interacts with their developing understanding of the social world. I use behavioral experiments, computational tools, and novel measurement methods like large-scale web-based studies, eye-tracking, and head-mounted cameras.
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Philipp Frank
Postdoctoral Scholar, Physics
BioPhilipp Frank is an Astronomy and Machine Learning researcher who is developing and applying statistical and ai methods to help deepen our understanding of the structure of the Milky Way and the Cosmos. He did his PhD and a followup Postdoc in Germany at Ludwig Maximilians University and the Max-Planck-Institute for Astrophysics where he worked on probabilistic ML and numerical inference methods and contributed to applications ranging from radio interferometry, X- and gamma-ray imaging, Cosmic Ray air-shower reconstructions, and 3d maps of the dust and gas content of our local Galactic neighborhood.
As a KIPAC Fellow at Stanford he aims to push 3D mapping of the interstellar medium to unprecedented scales in both size and resolution, and incorporate multiple additional tracers for a more comprehensive picture of local structures. This aims to shed light on the mechanisms of star formation and galaxy dynamics across scales only accessible through our unique vantage point within the Galaxy. -
Hunter Fraser
Professor of Biology
Current Research and Scholarly InterestsWe study the evolution of complex traits by developing new experimental and computational methods.
Our work brings together quantitative genetics, genomics, epigenetics, and evolutionary biology to achieve a deeper understanding of how genetic variation shapes the phenotypic diversity of life. Our main focus is on the evolution of gene expression, which is the primary fuel for natural selection. Our long-term goal is to be able to introduce complex traits into new species via genome editing.
