Chief Data Officer and Institute Scientist
Co-Director, Eric and Wendy Schmidt Center
Broad Institute of MIT and Harvard
Anthony Philippakis is the chief data officer of the Broad
Institute of MIT and Harvard, and the co-director of the Eric and Wendy Schmidt Center.
He trained as a cardiologist at Brigham and Women’s Hospital, with
a focus on rare genetic cardiovascular diseases. At the Broad Institute he is
the founding director of the Data Sciences Platform, an organization of over
200 software engineers and computational biologists that develops software for
analyzing genomic and clinical data. In addition to his roles at the Broad
Institute and Brigham and Women’s Hospital, Philippakis is a venture partner at
GV, focusing on machine learning, distributed computing, and genomics.
Philippakis received his M.D. from Harvard Medical School and
completed a Ph.D. in biophysics at Harvard. As an undergraduate, he studied
mathematics at Yale University, and later completed the Part III (equivalent to
M.Phil.) in mathematics at Cambridge University.
Chief Data Officer and Institute Scientist
Co-Director, Eric and Wendy Schmidt Center
Broad Institute of MIT and Harvard
Anthony Philippakis is the chief data officer of the Broad
Institute of MIT and Harvard, and the co-director of the Eric and Wendy Schmidt Center.
He trained as a cardiologist at Brigham and Women’s Hospital, with
a focus on rare genetic cardiovascular diseases. At the Broad Institute he is
the founding director of the Data Sciences Platform, an organization of over
200 software engineers and computational biologists that develops software for
analyzing genomic and clinical data. In addition to his roles at the Broad
Institute and Brigham and Women’s Hospital, Philippakis is a venture partner at
GV, focusing on machine learning, distributed computing, and genomics.
Philippakis received his M.D. from Harvard Medical School and
completed a Ph.D. in biophysics at Harvard. As an undergraduate, he studied
mathematics at Yale University, and later completed the Part III (equivalent to
M.Phil.) in mathematics at Cambridge University.
Journal article
No abstract
Journal article
Fibrotic diseases affect multiple organs and are associated with morbidity and mortality. To examine organ-specific and shared biologic mechanisms that underlie fibrosis in different organs, we developed machine learning models to quantify T1 time, a marker of interstitial fibrosis, in the liver, pancreas, heart and kidney among 43,881 UK Biobank participants who underwent magnetic resonance imaging. In phenome-wide association analyses, we demonstrate the association of increased organ-specific...
