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Anthony Philippakis

M.D., Ph.D.

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. 

Anthony Philippakis

M.D., Ph.D.

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. 

Recent Publications

Machine learning-driven spleen imaging and genomics uncover a splenic connection to coronary artery disease

Published On 2026 Sep 09

Journal article

Despite advances in managing traditional risk factors, coronary artery disease (CAD) remains the leading cause of mortality. Circulating hematopoietic cells influence risk for CAD separately from traditional risk factors, but the role of a key regulating organ, the spleen, is unknown. The understudied spleen is a representation of the hematopoietic system optimally suited for unbiased radiologic investigations toward mechanistic insights. Here, we leveraged deep learning to extract 107 splenic...


Machine learning cross-platform proteomic imputation enables protein quality scoring and replication of epidemiological associations

Published On 2026 May 18

Journal article

High-throughput affinity-based proteomics has advanced biomedical research, yet fundamental, persistent discordance between mainstream platforms (SomaScan and Olink) routinely undermines the replication of findings. This platform-driven non-replication complicates downstream biological validation and biomarker prioritization. Here, we develop a machine learning-based framework for cross-platform protein value imputation to resolve this translational bottleneck. Using paired proteomic data...