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Saeed Hassanpour, PhD

Professor of Biomedical Data Science
Professor of Epidemiology

Additional Titles/Positions/Affiliations
Professor of Computer Science

Biomedical Data Science

PhD in in Electrical Engineering/Biomedical Informatics, Stanford University, Stanford, CA
MMath in Computer Science, University of Waterloo, Waterloo, Canada
BS in Computer Engineering, Sharif University of Technology, Tehran, Iran

Dartmouth Cancer Center
Quantitative Biomedical Sciences


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Contact Information

Williamson Translational Research Building
One Medical Center Drive
HB 7261
Lebanon NH 03756

Email: Saeed.Hassanpour@Dartmouth.edu


Dr. Saeed Hassanpour is the Founding Director of Dartmouth Center for Precision Health & Artificial Intelligence (CPHAI) and a Professor in the Departments of Biomedical Data Science, Computer Science, and Epidemiology at Dartmouth. His research is focused on building novel machine learning and multimodal data analysis methods to inform precision health, and his lab has been a pioneer in advancing digital pathology through deep learning methodologies. Dr. Hassanpour has led multiple NIH-funded research projects on developing new machine learning models for medical image analysis and clinical text mining to improve diagnosis, prognosis, and personalized therapies. His research has resulted in numerous publications, software, and datasets that are widely recognized and have received multiple awards, including the 2019 Agilent Early Career Professor Award for breakthroughs in digital pathology. Dr. Hassanpour currently serves as a standing member on multiple national and international scientific panels and committees, such as NIH's Clinical Data Management and Analysis (CDMA) Study Section and the JAMIA Open Editorial Board. Before joining Dartmouth, he worked as a Research Engineer at Microsoft. Dr. Hassanpour received his PhD in Electrical Engineering with a minor in Biomedical Informatics from Stanford University and completed his postdoctoral training at the Stanford Center for Artificial Intelligence in Medicine and Imaging.