Danielle Pace
Senior Machine Learning Scientist
Danielle Pace is a senior machine learning scientist in the Machine Learning for Health team at the Ó³»´«Ã½ of MIT and Harvard. She develops machine learning models that use large clinical datasets, including medical images, electronic health records, ECGs, and genetics, to better understand disease, learn useful data representations, and predict disease risk.
Pace earned her Ph.D. in computer science from MIT, where she created machine learning models to segment cardiac scans of patients with severe congenital heart defects. She also holds a B.Cmp.H. degree in biomedical computing from Queen's University, Canada, and an M.E.Sc. degree in biomedical engineering from the University of Western Ontario, Canada. Before her doctoral studies, she worked as a medical imaging researcher and software developer at Kitware Inc. Afterwards, she conducted postdoctoral research at the A.A. Martinos Center at Massachusetts General Hospital, where she developed segmentation and anatomical modeling models for neuroimaging data.
June 2025
