Stanford University
Showing 1-4 of 4 Results
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Tracy Lam-Hine
Postdoctoral Scholar, Epidemiology
BioTracy Lam-Hine (he/him), DrPH, MBA, is a postdoctoral scholar in the Department of Epidemiology and Population Health and the Center for Population Health Sciences, a Research Education Component Fellow at the Stanford Alzheimer's Disease Research Center, and is affiliated via a Research Fellowship with the Temple University Center for Public Health Law Research. Dr. Lam-Hine is a social epidemiologist and population health scientist, studying how exposure to adverse childhood experiences, policy environments, and mid-life chronic disease burden shape the risk cognitive and functional aging in later life. Within this broad research area, he has a special focus on the health and social experiences of the US Multiracial population, surveillance data, methods to improve descriptive and population-generalizable research.
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Zongbo Li
Postdoctoral Scholar, Health Policy
BioZongbo Li, PhD, is a postdoctoral researcher at Stanford Health Policy. His research focuses on applying simulation modeling and cost-effectiveness analysis to inform policy decisions related to substance use and infectious diseases. He evaluates overdose prevention interventions, including naloxone distribution and medications for opioid use disorder, with particular attention to vulnerable populations such as people who are incarcerated. His work also encompasses modeling infectious diseases and evaluating interventions for COVID-19, HIV, and HCV. Zongbo earned his PhD in Health Services Research, Policy & Administration from the University of Minnesota.
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Lili Liu
Postdoctoral Scholar, Epidemiology
BioLili (Larry) Liu, PhD, is a postdoctoral fellow in the Department of Epidemiology and Population Health at Stanford University. Dr. Liu is an integrative epidemiologist whose research is unified by a consistent methodological approach rather than a single disease area. Across his master’s, doctoral, and postdoctoral training, he has repeatedly developed or operationalized epidemiologic frameworks and analytic programs and applied them to important public health questions spanning rare diseases, chronic disease, cancer, mortality, microbiome, and women’s health. His work brings together molecular biomarkers, large-scale population cohorts, and real-world health data to generate coherent, hypothesis-driven research on how genetic variation, lifestyle, pharmacologic factors, and early-life exposures shape inflammation, biological aging, and chronic disease risk across the life course.
During his master’s training at Peking University, Dr. Liu developed expertise in literature synthesis, national claims-based study, rare disease burden estimation, patient-centered health information research, cohort-based analysis, and vaccine effectiveness evaluation. He helped build and apply claims-based analytic algorithms to estimate incidence and prevalence for multiple rare diseases in China, led first-author studies on online health information and patient information needs in rare disease populations, and established an analytic framework for CHARLS-based cohort studies that supported multiple downstream projects. During his PhD training at Vanderbilt University, he expanded into population genetics, molecular and cancer epidemiology, mortality and health disparities research, gut microbiome, and pooled multi-study analyses. His doctoral work included a multi-ancestry GWAS of urinary prostaglandin E2 metabolite (PGE-M), development of PGE-M-derived dietary and lifestyle scores, and Mendelian randomization analyses linking lipid-related pathways to colorectal cancer risk. He also led several first-author studies in the Southern Community Cohort Study on poverty, sitting time, physical activity, walking and mortality, and alcohol intake and the gut microbiome, several of which received substantial public health and media attention.
At Stanford, Dr. Liu has developed an independent research program centered on women’s health and life-course epidemiology using U.S. national claims data. He has built large nationwide pregnancy and mother-baby cohorts from MarketScan to study adverse obstetric outcomes, long-term cardiometabolic and hepatic outcomes, and early-onset cancer risk. His first corresponding-author paper at Stanford examined gestational diabetes in relation to subsequent type 2 diabetes and metabolic dysfunction-associated steatotic liver disease, and his ongoing work extends this framework to cardiovascular, kidney, metabolic, and reproductive health outcomes, including PCOS and endometriosis. He also received a Stanford MCHRI fellowship grant to study prenatal and early-life antibiotic exposure in relation to pediatric inflammatory bowel disease and celiac disease. In parallel, his collaborative work includes placental and maternal-fetal research on extracellular vesicles and angiogenic signaling.
Methodologically, Dr. Liu works at the interface of causal inference, pharmacoepidemiology, molecular epidemiology, and scalable real-world data science, using reproducible analytic pipelines in R, Python, SQL, and high-performance computing environments. Across all stages of his training, the central theme of his work has been to build scalable analytic infrastructure and apply it to high-impact epidemiologic questions with broad public health relevance, with the overarching goal of translating rigorous population science into actionable strategies for chronic disease prevention in diverse populations.
