Natural language processing and text mining are increasingly important tools for understanding public health concerns, tracking disease sentiment, and predicting population health trends. My lab combines deep learning, transformer models, and interpretable NLP techniques to extract meaningful insights from unstructured health-related data.
Our work bridges computational linguistics and epidemiology, enabling early detection of health concerns and a quantifiable measure of public sentiment around vaccines, disease outbreaks, and health interventions.