Sarah M. Preum
Assistant Professor
Appointments
Assistant Professor of Computer Science
Technical Associate Director, Dartmouth Center for Precision Health and Artificial Intelligence
Adjunct Faculty, Department of Biomedical Data Science, Geisel School of Medicine
Area of Expertise
Natural Language Processing,
Human-AI Interaction,
Multimodal AI,
Social Computing,
Computational Health
Biography
I am a researcher in Natural Language Processing, Human–AI Interaction, and Computational Health, advancing socio-technical AI that reduces cognitive burden and promotes equity in communication-rich, high-stakes domains. I have authored 59 peer-reviewed papers (34 as the lead PI/first author) in premier Computer Science venues such as ACL, EMNLP, AAAI, CHI, IMWUT, ICWSM, and ACM Computing Surveys (impact factor: 23.8). Recognized as a Google Research Scholar (2025) and EECS Rising Star (2020) with multiple Best Paper nominations, I serve as an Associate Editor for ACM Transactions on Computing for Healthcare. I have also served as area chair in ACL, EMNLP, and NeurIPS. I have organized international workshops on reliability of large language models (LLMs) and AI in healthcare.
I have mentored graduate and undergraduate students toward placements at Google, Abridge, Salesforce, MIT, Caltech, Columbia, and Harvard. My lab develops domain-informed, human-centered NLP methods, systems, and metrics, and leverages large-scale multimodal behavioral and clinical data and interdisciplinary collaboration to build and evaluate adaptive, uncertainty-aware systems for patient–provider messaging, online health communities, and digital health research. My work emphasizes reproducibility, resulting in 14 public datasets and open-source resources. My research, supported by NIH, Google, National Center for Advancing Translational Sciences, NSF, and institutional grants, engages diverse stakeholders across the U.S. and Global South to advance equitable communication and well-being through socio-technical AI systems.
Education
Ph.D. University of Virginia
M.Sc. University of Virginia
B.Sc. Bangladesh University of Engineering and Technology
Taught Courses
Publications
Joseph Gatto, Omar Sharif, Parker Seegmiller, Sarah M. Preum. Large Language Models for Document-Level Event-Argument Data Augmentation for Challenging Role Types. The 63rd Annual Meeting of the Association for Computational Linguistics (ACL) 2025. (Nominated for best paper)
Joseph Gatto, Parker Seegmiller, Timothy Burdick, Inas S. Khayal, Sarah DeLozier, Sarah M. Preum. Follow-up Question Generation For Enhanced Patient-Provider Conversations. The 63rd Annual Meeting of the Association for Computational Linguistics (ACL) 2025.
Parker Seegmiller, Joseph Gatto, Sarah Greer, Ganza Belise Isingizwe, Rohan Ray, Timothy Burdick, Sarah M. Preum. How Much Would a Clinician Edit This Draft? Evaluating LLM Alignment for Patient Message Response Drafting. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026.
Parker Seegmiller, Sarah M. Preum. Measuring the Effects of Natural Shifts in User Prompt Distribution on Large Language Model Performance. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026.
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.
Joseph Gatto, Omar Sharif, Sarah M. Preum. Chain-of-Thought Embeddings for Stance Detection on Social Media. Proceedings of the International Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.
Madhusudan Basak, Omar Sharif, Sarah E. Lord, Jacob T. Borodovsky, Lisa A. Marsch, Sandra A. Springer, Edward Nunes, Charlie D. Brackett, Luke J. Archibald, Sarah M. Preum. Information Needs for Opioid Use Disorder Treatment Using Buprenorphine Product: Qualitative Analysis of Suboxone-Focused Reddit Data. Journal of Medical Internet Research (JMIR), 2025
Parker Seegmiller, Sarah M. Preum. Statistical Depth for Ranking and Characterizing Transformer-Based Text Embeddings. Proceedings of the International Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.
Omar Sharif, Joseph Gatto, Madhusudan Basak, Sarah M. Preum. Explicit, Implicit, and Scattered: Revisiting Event Extraction to Capture Complex Arguments. Proceedings of the International Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
Omar Sharif, Madhusudan Basak, Tanzia Parvin, Ava Scharfstein, Alphonso Bradham, Jacob Borodovsky, Sarah Lord, Sarah M. Preum. Characterizing Information Seeking Events in Health-Related Social Discourse. The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024.
Bushra Hossain, Sarah M. Preum, Md Fazle Rabbi, Rifat Ara, Mohammed Eunus Ali. Subreddit to Symptomatology: A Lexicon-based Approach to Extract Symptoms of Complex Conditions from Online Discourse. Journal of Medical Internet Research (JMIR), 2025.
Will Romano, Omar Sharif, Madhusudan Basak, Joseph Gatto, and Sarah M. Preum. Theme-driven Keyphrase Extraction to Analyze Social Media Discourse. Proceedings of the AAAI Conference on Web and Social Media (ICWSM). 2024
Speaking Engagements
When Ground Truth Is a Distribution: New Tasks and Evaluation Paradigms for Asynchronous, High-Stakes Communication. Colloquium at Computational Health Informatics Program (CHIP), Spring 2026, Harvard University.
When Ground Truth Is a Distribution: New Tasks and Evaluation Paradigms for Asynchronous, High-Stakes Communication. NLP Seminar, Department of Computer Science, Spring 2026, Columbia University.
When Ground Truth Is a Distribution: New Tasks and Evaluation Paradigms for Asynchronous, High-Stakes Communication. Language Technology Institute Colloquium, Spring 2026, Carnegie Mellon University.
From Cognitive Burden to Collaborative Intelligence: Socio-Technical AI for Clinical Communication. Human Computer Interaction Institute Colloquium, Spring 2026, Carnegie Mellon University.
From Cognitive Burden to Collaborative Intelligence: Socio-Technical AI for Clinical Communication. Center for Technology and Behavioral Health Seminar (CTBH) Series, Fall 2025.
From Cognitive Burden to Collaborative Intelligence: Socio-Technical AI for Clinical Communication. SYNERGY Translational and Learning Health System Science Collaborative Seminar Series, Fall 2025, Dartmouth Clinical and Translational Science Institute.
In-Context Learning for Human-AI Collaboration: Methods and Measures. Network Science Institute Colloquium, Department of Computer Science, Fall 2024, Northeastern University.
Unveiling the Journey: Analyzing Information Seeking Events in Online Recovery Discourse. Center for Technology and Behavioral Health Seminar Series, Fall 2023.
Intelligent Assistants for Improved Health: Teaching Machines to Understand Data. Biomedical Data Science Grand Rounds, Geisel School of Medicine, Winter 2022, Dartmouth College.
Navigating academic research in Computer Science: through the lens of an outlier. Preparation for Research through Immersion, Skills, and Mentorship (PRISM) seminar, Department of Computer Science, Spring 2021, University of Toronto
Information Extraction & Fusion for Improving Personal & Public Health Safety, Senseable City Lab, Spring 2020, Massachusetts Institute of Technology (MIT).
Information Extraction & Fusion for Improving Personal & Public Health Safety, Human-centered Artificial Intelligence Center, Spring 2020, Stanford University.
Works in Progress
Selected Works & Activities
Contact