Research

Biomedical AI

In biomedical AI, my research focuses on applying natural language processing, large language models, and reinforcement learning to clinical text and electronic health records. I develop methods to extract medical knowledge, answer clinical questions, and predict patient risks, including drug overdose and substance use disorders. I also mine social media data, such as posts from Reddit communities, to identify emerging opioid- and drug-related public health risks using large language models. Overall, I aim to build practical and trustworthy AI systems that support clinical decision-making and inform healthcare policy.

🎯 Publications

Yuhang Jiang, Md Sultan Al Nahian, Li Hao Richie Xu, Rani Chikkanna and Ramakanth Kavuluru. “LitTx: A New Treatment Relation Extraction Dataset” . In Proceedings of the fifteenth biennial Language Resources and Evaluation Conference (LREC 2026)
Md Sultan Al Nahian, Ramakanth Kavuluru. “RadQA-DPO: A Radiology Question Answering System with Encoder-Decoder Models Enhanced by Direct Preference Optimization” In Proceedings of the 24th Workshop on Biomedical Language Processing, Association for Computational Linguistics (ACL 2025)
Motasem Obeidat, Md Sultan Al Nahian, Ramakanth Kavuluru. “Do LLMs Surpass Encoders for Biomedical NER?” In Proceedings of the 13th IEEE International Conference on Healthcare Informatics (2025)
Vinu Ekanayake, Md Sultan Al Nahian, Ramakanth Kavuluru. “Mining Social Media for Barriers to Opioid Recovery with LLMs” CL4Health at The Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL) 2025
Motasem Obeidat, Vinu Ekanayake, Md Sultan Al Nahian, Ramakanth Kavuluru. “Language Model Methods for Health Entity Tagging and Classification on Social Media (Tasks 4 & 5)”. In Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks (2024).

Preprint and Under-review

Md Sultan Al Nahian, Chris Delcher, Daniel Harris, Peter Akpunonu, Ramakanth Kavuluru. “Large Language Models for Drug Overdose Prediction from Longitudinal Medical Records” (2025).
Motasem S Obeidat, Peter Akpunonu, Daniel Harris, Md Sultan Al Nahian, Chris Delcher and Ramakanth Kavuluru. “On Predictive Models for Forecasting Buprenorphine Therapy Discontinuation among Patients with Opioid Use Disorder” (Currently under review at Artificial Intelligence in Medicine (AIME) 2026).

AI Value Alignment and Reinforcement Learning

With the rapid advancement of AI, there is growing concern that AI systems may unintentionally violate human interests and well-being. For the safe integration of AI across various domains, AI agents must understand human values and preferences and align with them. To address these challenges, my research focuses on developing machine learning techniques that apply Natural Language Processing and Reinforcement Learning to enable AI agents to make decisions without violating human values. Additionally, I work on reinforcement learning and multi-agent reinforcement learning to develop methods that make the training of RL agents more stable and efficient.

🎯 Publications

Md Sultan Al Nahian, Tasmia Tasrin, Spencer Frazier, Mark Riedl, and Brent Harrison. “The Goofus & Gallant Story Corpus for Practical Value Alignment”. In Proceedings of the 23rd IEEE International Conference on Machine Learning and Applications (2024).
Md Sultan Al Nahian, Spencer Frazier, Mark Riedl, and Brent Harrison. “Training Value-Aligned Reinforcement Learning Agents Using a Normative Prior”. In IEEE Transactions on Artificial Intelligence (2023).
Tasmia Tasrin, Md Sultan Al Nahian, Habarakadage Perera, and Brent Harrison. “Influencing Reinforcement Learning through Natural Language Guidance”, In Proceedings of the 34th International FLAIRS Conference (2021).
Md Sultan Al Nahian, Spencer Frazier, Mark Riedl, and Brent Harrison. “Learning Norms from Stories: A Prior for Value Aligned Agents”, In Proceedings of the 3rd AAAI/ACM Conference on AI, Ethics, and Society (2020).

Multi-modal Machine Learning

I also conduct research in multi-modal machine learning, focusing on integrating vision and language to enable deeper semantic understanding of visual content.

🎯 Publications

Md Sultan Al Nahian, Tasmia Tasrin, and Brent Harrison. “Visual Question Answering Using Semantic Information from Image Descriptions”, In Proceedings of the 34th International FLAIRS Conference (2021).
Md Sultan Al Nahian, Tasmia Tasrin, Sagar Gandhi, Ryan Gaines, and Brent Harrison. “A Hierarchical Approach for Visual Storytelling Using Image Description”, in Proceedings of the International Conference on Interactive Digital Storytelling (2019).

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