Research
We develop NLP and machine learning methods to uncover insights about health attitudes, behaviors, and outcomes — with a focus on health disparities and mental wellbeing. Our work spans social media, clinical language, and mobile sensing across diverse global populations.
Research Themes
Mental Health & Social Media
Using large-scale social media language to detect, monitor, and understand depression, anxiety, loneliness, and other mental health conditions at individual and community levels.
Global Health & Vaccine Acceptance
Developing computational models that capture health attitudes across cultures and languages — including vaccine hesitancy, health misinformation, and precision public health messaging.
Health Disparities & Equity
Investigating racial, geographic, and socioeconomic disparities in health outcomes and healthcare quality using online reviews, social media, and clinical data.
Firearms Safety & Public Health
Characterizing online discourse around firearms, suicide risk, and safety messaging to inform evidence-based public health policy.
Digital Phenotyping
Combining passive mobile sensing, language, and behavioral data to build richer models of individual health trajectories and intervention outcomes.
AI for Health Communication
Designing and evaluating LLM-based systems for patient education and health coaching — with a focus on preserving human agency and ensuring equitable outcomes.