Sarah Masud Preum
Assistant Professor of Computer Science
Adjunct Faculty, Department of Biomedical Data Science, Geisel School of Medicine
Faculty Affiliate, Center for Technology and Behavioral Health (CTBH)
Technical Associate Director, Dartmouth Center for Precision Health and Artificial Intelligence
I specialize in creating innovative and practical machine learning methods that drive advancements in computational health. My primary focus areas include natural language processing, temporal modeling, and human-AI interaction. I'm passionate about leveraging these techniques to deliver personalized decision support tailored to specific digital health applications. Please visit my website for more details.
Biomedical Data Science, Computer Science
- B.Sc. Bangladesh University of Engineering and Technology
- M.Sc. University of Virginia
- Ph.D. University of Virginia
Joseph Gatto, Madhusudan Basak, and Sarah Masud Preum. "Scope of Pre-trained Language Models for Detecting Conflicting Health Information." In Proceedings of the International AAAI Conference on Web and Social Media, vol. 17, pp. 221-232. 2023.
Sarah M. Preum, Sirajum Munir, Meiyi Ma, Mohammad Yasar, David J. Stone, Ronald D. Williams, Homa Alemzadeh, and John Stankovic. "A Review of Cognitive Assistants for Healthcare: Trends, Prospects, and Future Directions." ACM Computing Surveys, 2021 [Impact factor: 6.131]
Sarah M. Preum, Homa Alemzadeh, and John Stankovic. "EMSContExt: EMS Protocol-driven Concept Extraction for Cognitive Assistance in Emergency Response." Proceedings of the AAAI Conference on Artificial Intelligence, 2020
Sarah M. Preum, Md A. Mondol, Meiyi Ma, Hongning Wang, John Stankovic. "PreCluDe: Conflict Detection in Textual Health Advice." IEEE International Conference on Pervasive Computing and Communications (PerCom), 2017 [CORE rank: A*, acceptance rate 16.5%]
Works In Progress
Selected Works & Activities