Avijit Mitra

PhD Student

CICS, UMass Amherst

About Me

Hello there, I'm Avijit, Welcome to my personal website! I am an applied scientist at Amazon. I earned my PhD in Computer Science from the Manning College of Information And Computer Sciences at the University of Massachusetts Amherst where I was advised by Professor Hong Yu in the UMass BIONLP Lab. I also hold an MSc in computer science from UMass Amherst, as well as both a BSc and MSc in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (BUET).

With a strong foundation in both engineering and computer science, I've had the privilege of interning at Amazon for four consecutive summers. My research centers on Natural Language Processing (NLP) in the healthcare domain, particularly leveraging clinical data such as Electronic Health Record (EHR) notes to build practical and impactful systems.

Before embarking on my PhD journey, I contributed as a Machine Learning Researcher at Semion, where I focused on developing and deploying AI-driven solutions for healthcare. My passion lies at the intersection of cutting-edge technology and its transformative impact on healthcare, and I am deeply committed to advancing the use of NLP to improve healthcare outcomes.

Research Interests

Natural Language Processing
Bioinformatics
Epidemiology
Machine Learning

Education

PhD in Computer Science, 2025

University of Massachusetts Amherst
MSc in Computer Science, 2024

University of Massachusetts Amherst
MSc in Electrical and Electronic Engineering, 2021

Bangladesh University of Engineering and Technology
BSc in Electrical and Electronic Engineering, 2017

Bangladesh University of Engineering and Technology

Selected Publications

A. Mitra, Z. Yang, E. Druhl, R. Goodwin, H. Yu., “ynth-SBDH: A Synthetic Dataset of Social and Behavioral Determinants of Health for Clinical Text”, EMNLP main, 2025
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A. Mitra, K. Chen, W. Liu, R.C. Kessler, H. Yu, “Post-discharge Suicide Prediction Among US Veterans Using Natural Language Processing-enriched Social and Behavioral Determinants of Health”, npj Mental Health Research, 2025
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C. León, M.L. Sung, J. I. Reisman, W. Liu, R.D. Kerns, K.S. Gordon, A. Mitra, S. Kwon, H. Yu, W.C. Becker, W. Li, “Occurrence of opioid related neurocognitive symptoms associated with long-term opioid therapy”, The Clinical Journal of Pain, 2025
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M.L. Sung*, C. León*, J.I. Reisman, K.S. Gordon, R.D. Kerns, W. Li, W. Liu, A. Mitra, H. Yu, W.C. Becker, “Disparities in receipt of medications for opioid use disorder before and during the COVID-19 pandemic in the U.S. Veterans Health Administration”, Substance Use & Addiction Journal, 2024
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A. Mitra, N. Gupta, C. Naik, A. Sethy, K. Bice, Z. Raeesy, “Generating contextual images for long-form text”, LREC-COLING, 2024
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P. Vashisht, A. Lodha, M. Maddipatla, Z. Yao, A. Mitra, Z. Yang, J. Wang, S. Kwon, H. Yu, “UMass-BioNLP at MEDIQA-M3G 2024: DermPrompt–A Systematic Exploration of Prompt Engineering with GPT-4V for Dermatological Diagnosis”, 6th Clinical Natural Language Processing Workshop @ ACL, 2024
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Z. Yang, A. Mitra, S. Kwon, H.Yu, “ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes”, 6th Clinical Natural Language Processing Workshop @ ACL, 2024
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Z. Yang, A. Mitra, W. Liu, D. Berlowitz, H.Yu, “TransformEHR: Transformer-based encoder-decoder generative model to enhance prediction of disease outcomes using electronic health records”, Nature Communications, 2023
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J. Wang, Z. Yao, A. Mitra, S. Osebe, Z. Yang, H. Yu, “UMASS BioNLP at MEDIQA-Chat 2023: Can LLMs generate high-quality synthetic note-oriented doctor-patient conversations?”, 5th Clinical Natural Language Processing Workshop @ ACL, 2023
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A. Mitra, R. Pradhan, R. D. Melamed, K. Chen, D. C. Hoaglin, K. L. Tucker, J. I. Reisman, Z. Yang, W. Liu, J. Tsai, H. Yu, “Associations Between Natural Language ProcessingEnriched Social Determinants of Health and Suicide Death Among US Veterans”, JAMA Network Open, 2023
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Z. Yang, S. Wang, B. P. S. Rawat, A. Mitra, H. Yu, “Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding”, EMNLP Findings, 2022
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A. J. Rose, J. S. Lee, D. R. Berlowitz, W. Liu, A. Mitra, H. Yu, “Guideline-discordant dosing of direct-acting oral anticoagulants in the veterans health administration”, BMC Health Services Research, 2021
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A. Mitra, H. Ahsan, W. Li, W. Liu, R. D. Kerns, J. Tsai, W. Becker, D. A. Smelson, H. Yu, “Risk Factors Associated With Nonfatal Opioid Overdose Leading to Intensive Care Unit Admission: A Cross-sectional Study”, JMIR Medical Informatics, 2021
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H. Ahsan, E. Ohnuki, A. Mitra, H. Yu, “MIMIC-SBDH: A Dataset for Social and Behavioral Determinants of Health”, Machine Learning for Healthcare, 2021
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A. Mitra, B. P. S. Rawat, D. McManus, H. Yu, “Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study”, JMIR Medical Informatics, 2021
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A. Mitra, B. P. S. Rawat, D. McManus, A. Kapoor, H. Yu, “Bleeding Entity Recognition in Electronic Health Records: A Comprehensive Analysis of End-to-End Systems”, AMIA Annual Symposium, 2020
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A. Mitra, K. Ashraf, "Sepsis Prediction and Vital Signs Ranking in Intensive Care Unit Patients", arXiv preprint arXiv:1812.06686, 2018
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R. Ahsan, A. Mitra, S. Omar, M. Z. R. Khan, M. A. Basith, "Sol−gel synthesis of DyCrO₃ and 10% Fe-doped DyCrO₃ nanoparticles with enhanced photocatalytic hydrogen production abilities", RSC Advances, 2018
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