School of Medicine
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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, and a T32 trainee in the Division of Endocrinology, Gerontology, and Metabolism. Dr. Lam-Hine is a social and legal epidemiologist, studying how exposure to adverse childhood experiences and policy environments shape the risk of chronic disease and aging outcomes across the life course. Within this broad research area, he has a special focus on the health and social experiences of the US Multiracial population and the measurement of structural racism in policy. Dr. Lam-Hine also collaborates with state and local health jurisdictions in California and Hawaii in applied epidemiology and surveillance projects on topics including structural racism, adolescent health, and COVID-19.
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Lili Liu
Postdoctoral Scholar, Epidemiology
BioLili (Larry) Liu, PhD, is a postdoctoral fellow in the Department of Epidemiology & Population Health at Stanford University. As an integrative epidemiologist, Dr. Liu unifies molecular biomarkers, large-scale population cohorts, and real-world health data into coherent, hypothesis-driven research with a sustained focus on how early-life exposures, genetic variation, lifestyle, and pharmacological factors shape inflammation, biological aging, and chronic disease risk across the life course. Trained in cancer genetic and nutrition epidemiology with complementary expertise in pharmacoepidemiology, his doctoral research at Vanderbilt University included a multi-ancestry GWAS of urinary prostaglandin E2 metabolite (PGE-M), development of PGE-M–derived dietary and lifestyle scores via elastic net with extensive bootstrapping, and Mendelian randomization analyses linking PGE-M to colorectal cancer across ancestries. At Stanford, Dr. Liu extends his research to maternal–fetal and placental epidemiology, building nationwide claims-based pregnancy cohorts (e.g., MarketScan) to examine gestational diabetes and downstream liver disease risk, and creating mother–infant pair cohort to investigate systemic antibiotic exposure in relation to subsequent inflammatory bowel disease and celiac disease. Parallel collaborations focus on extracellular vesicles and angiogenic signaling in placental health. Methodologically, Dr. Liu works at the interface of causal inference, pharmacoepidemiology, and machine learning with reproducible data engineering (R/Python, SQL, HPC), with the overarching goal of translating mechanistic insights into actionable biomarkers and risk tools for chronic disease prevention in diverse populations.