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Mahnaz Maddah is the director of Machine Learning for Health (ML4H) at the Ó³»­´«Ã½ of MIT and Harvard, where she leads a multidisciplinary team of scientists and engineers developing AI methods to improve disease diagnosis, prognosis, and risk prediction. Working in close collaboration with clinicians from Mass General Brigham and other healthcare institutions, Maddah’s team builds machine learning tools that leverage imaging, electrocardiograms, and clinical notes to advance biomedical discovery and patient care. She has served as principal investigator on several grants, including a NIH Direct-to-Phase II SBIR award for a computer vision platform for non-invasive characterization of cardiomyocytes and a NIH-funded initiative to develop FAIR multimodal AI for disease prediction using All of Us data. 

Maddah has received numerous honors and leadership appointments, including membership on the scientific advisory board for the Ó³»­´«Ã½ Machine Learning in Drug Discovery Symposium and the Ó³»­´«Ã½â€™s Generative AI Working Group. She has chaired scientific sessions on clinical AI and mentors emerging innovators through programs such as MIT Sandbox Innovation Fund and MIT Catalyst.

Maddah earned her Ph.D. in electrical engineering and computer science from MIT, conducting research in medical image analysis at the Computer Science and Artificial Intelligence Lab (CSAIL) and Harvard Medical School. She also holds M.S. and B.S. degrees in electrical engineering from the University of Tehran. Prior to joining Ó³»­´«Ã½, she co-founded multiple AI-driven health startups and held research roles at GE Global Research and SRI International.