Research Areas

Multi-modal Modeling Across Healthcare

Clinical care generates diverse forms of data, including pathology slides, imaging, laboratory values, and clinical documentation. Each modality provides unique and complementary information about a patient's condition. Our work focuses on developing multi-modal approaches that leverage the full spectrum of medical data to deliver precise, robust, and clinically actionable insights across diagnosis, prognosis, and treatment decision-making.

Patient-Facing Chatbots

Large Language Models (LLMs) are increasingly being explored for enhancing patient communication by simplifying and explaining complex medical reports, such as X-ray findings and hospital discharge summaries. We focus on designing and evaluating Al systems that generate accurate, understandable, and clinically safe explanations for patients.

Advancing Dermatological Research

We work to advance dermatological research by building new datasets, developing predictive models, and designing clinical tools that improve patient care. Our efforts span outcomes prediction, biomarker discovery, imaging analysis, and patient-centered studies. Recognizing the challenges of limited diversity in existing dermatology resources, we prioritize inclusive approaches that capture the full range of skin types and clinical presentations. Our goal is to advance across the spectrum of dermatologic diseases.