Shelley H Liu, PhD
- ASSISTANT PROFESSOR | Population Health Science and Policy
Research Topics:Biostatistics, Environmental Health, Epidemiology, Pediatrics, Psychiatry, Public Health
Shelley H. Liu is an Assistant Professor in the Center for Biostatistics, Department of Population Health Science and Policy. Dr. Liu’s primary research interests are in longitudinal data analysis, Bayesian analysis, latent class analysis, environmental epidemiology and children’s health. Dr. Liu received her BA from Northwestern University in 2011, and her PhD in Biostatistics from Harvard University in 2016. During her doctoral training, she developed statistical methods for environmental health research. These projects included developing methods for estimating the health effects associated with exposure mixtures, and identifying critical time windows of vulnerability to exposures. For her dissertation research, she received a Distinguished Student Paper Award from the International Biometric Society - Eastern North America Region. She also received two National Science Foundation EAPSI awards to conduct research in Australia and China. Through these awards, she developed computationally efficient methods to analyze large longitudinal cohort data.
BA, Northwestern University
PhD, Harvard University
Student Paper Travel Award
Distinguished Student Paper Award
New Researcher Best Abstract Award
East Asia and Pacific Summer Institutes – China Fellowship
East Asia and Pacific Summer Institutes – Australia Fellowship
Rose Traveling Fellowship in Chronic Disease Epidemiology and Biostatistics
Liu SH, Bobb JF, Lee KH, Gennings C, Claus Henn B, Bellinger D, Austin C, Schnaas L, Tellez-Rojo MM, Wright RO, Arora M, Coull BA. Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures. Biostatistics 2017;.
Liu SH, Li Y, Liu B. Exploratory cluster analysis to identify patterns of chronic kidney disease in the 500 Cities Project. Preventing Chronic Disease 2017;.
Li Y, Liu SH, Li N, Liu B. Unhealthy behaviors, prevention measures, and neighborhood cardiovascular health: A machine learning approach. Journal of Public Health Management & Practice 2018;.