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Staff
Saurav Sengupta
Data Scientist
School of Data Science
Email: ss4yd@virginia.edu
Additional Contact Information
Saurav Sengupta is a data scientist at the University of Virginia School of Data Science, working with Professor Donald Brown to apply machine learning to challenging health care problems. Sengupta holds a Ph.D. in Data Science, and his research encompasses three primary areas: working on Vision Language Models (VLMs) for high resolution pathology images; the creation of interpretable deep learning approaches for risk factor analysis from electronic health records (EHRs); and analysis of time series data using machine learning to determine impact of targeted interventions.
His expertise encompasses computer vision, natural language processing, interpretable AI, and clinical dataset analysis, with publications accepted at esteemed conferences such as ICCV 2025 Workshops, IEEE ISBI 2024, and ML4H 2023. Before transitioning to Data Science, Saurav worked on developing web applications for banking systems.
Education
- Ph.D. in Data Science, University of Virginia, 2024
- M.S. in Data Science, University of Virginia, 2019
- Bachelors of Electrical Engineering 2016, Birla Institute of Technology and Science (India)
Selected Publications
[1] Sengupta, Saurav, and Donald E. Brown. "Automatic report generation for histopathology images using pre-trained vision transformers and BERT." 2024 IEEE International Symposium on Biomedical Imaging (ISBI). IEEE, 2024.
[2] Sengupta, Saurav, et al. "Determining Risk Factors for Long COVID Using Positive Unlabeled Learning on Electronic Health Records Data from NIH N3C." 2023 International Conference on Machine Learning and Applications (ICMLA). IEEE, 2023.
[3] Sengupta, Saurav, et al. "Analyzing historical diagnosis code data from NIH N3C and RECOVER Programs using deep learning to determine risk factors for Long Covid." 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2022.
[4] Moradinasab, Nazanin, Saurav Sengupta, Jiebei Liu, Sana Syed, and Donald E. Brown. "Towards robust multimodal representation: A unified approach with adaptive experts and alignment." arXiv preprint arXiv:2503.09498 (2025). Accepted at CVAMD@ICCV 2025.