Selected research themes are summarized below. A complete publication list is available on my Google Scholar profile.
Clinical Language Models & LLM Evaluation
My work in this area focuses on clinical language modeling, clinical NLP evaluation, and understanding the limits of LLMs in healthcare settings.
Knowledge-Infused Biomedical AI
This line of work studies how biomedical knowledge sources, ontologies, and structured medical concepts can improve clinical NLP and prediction models.
Graph Learning for Healthcare
This work applies graph neural networks, knowledge graphs, and multi-view representation learning to patient outcome prediction and healthcare data modeling.
Neuro-Symbolic AI
This research explores neuro-symbolic methods for entity linking, explainability, and structured reasoning over short text and clinical data.
Medical Informatics & Real-World Evidence
This work includes collaborations on clinical informatics, real-world data, cancer research, disease trajectories, and digital health evidence generation.