Dr. Mathew V. Kiang is an Instructor in the Department of Epidemiology and Population Health at Stanford University School of Medicine. He also works with Stanford’s Center for Population Health Sciences and is an FXB Fellow at the Harvard François-Xavier Bagnoud Center for Health and Human Rights.
His research lies at the intersection of computational social science and social epidemiology. Methodologically, his work revolves around combining disparate data sources in epidemiologically meaningful ways. More concretely, he works with individual-level, non-health data (e.g., GPS, accelerometer, and other sensor data from smartphones), traditional health data (e.g., health systems or death certificate data), and third-party data (e.g., cellphone providers or ad-tech data). To do this, he uses a variety of methods such as joint Bayesian spatial models, traditional epidemiologic models, dynamical models, and demographic analysis.
- Social Epidemiology
- Digital Phenotyping
- Health Inequalities
- ScD, Quantitative Methods & Social Epidemiology, Harvard University
- MPH, International Health, New York University
- BA, Sociology, San Diego State University