School of Medicine
Showing 1-10 of 15 Results
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Linda (Yu-Ling) Lan
Basic Life Research Scientist, Genetics
BioLinda Lan, DVM, PhD is a postdoctoral fellow in the Snyder Lab. Her research focuses on understanding long-term illness post-acute infections by using a combination of different types of data (multi-omics) and wearable technologies. Currently, Linda is working on three projects.
The first project involves studying the shared mechanisms of long COVID, ME/CFS, and PTLDS using smartwatches and micro-sampling. The second project involves examining the role of autoantibodies in long COVID patients and COVID vaccine side effects. The third project involves exploring the changes in the molecular and physiological responses of astronauts during short space flights using multi-omics and wearable devices.
Linda previously conducted her PhD research at the University of Chicago, where she studied memory B cell responses to a chimeric-based universal influenza virus vaccine candidate. In her leisure time, she enjoys running, hiking, and listening to audiobooks. -
Matthew Landry
Member, Maternal & Child Health Research Institute (MCHRI)
BioCurrent research focuses on identifying the optimal diet (or diets) for chronic disease prevention and addressing the challenges of designing, implementing and reporting clinical trials that test dietary patterns. Particularly interested behavioral interventions that promote plant-forward and plant-based diets. Passionate advocator for policies that address nutrition-related health inequalities particularly in low resource settings and/or with communities experiencing health inequalities related to food insecurity and structural disparities.
Assistant Professor of Population Health and Disease Prevention at University of California, Irvine (effective July 1, 2023) -
Jeehee Lee
Postdoctoral Scholar, Orthopedic Surgery
BioDr. Lee is a dedicated researcher in the field of biomedical engineering, driven by a strong desire to help individuals suffering from illnesses. With a particular interest in disease treatment and regeneration, she embarked on her journey in this field. During her doctoral studies, Dr. Lee focused on developing functional biomaterials by leveraging chemical bonding at interfaces. Her expertise in this area led her to successfully create functional medical devices. Currently, as a postdoctoral researcher at Stanford University, Dr. Lee is actively involved in drug screening using a bone-mimicking 3D in vitro cancer model that utilizes biomaterials. Her research is centered around the utilization of biomaterials to develop innovative approaches for tuning the communication between cells and biomaterials. By advancing in the field of biomaterials, Dr. Lee aims to facilitate a better understanding of cell-biomaterial interactions, with the ultimate goal of improving healthcare outcomes. With her passion for cutting-edge research and her commitment to the development of biomaterials, Dr. Lee is dedicated to making significant contributions to the field and shaping the future of healthcare.
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Yunkyeong Lee
Postdoctoral Scholar, Endocrinology and Metabolism
BioYun is a postdoctoral research scholar in the Translational Genomics of Diabetes Laboratory under the mentorship of Dr. Anna Gloyn. Since joining the lab in August 2022, she has been investigating type 2 diabetes (T2D) susceptible genes and their molecular mechanisms in pancreatic β-cell dysfunction and the development of T2D. Her primary focus is on how T2D effector transcripts alter autophagy/mitophagy pathways in human pancreatic β-cells, contributing to β-cell failure, mitochondrial dysfunction, and T2D pathology. She also investigated the impact of genetic mutations underlying neonatal diabetes using CRISPR HDR knockin genome editing in human induced pluripotent stem cell (hiPSC) models and their derivatives.
During her PhD, she explored the role of an epigenetic regulator and its molecular machinery in the pathogenesis of non-alcoholic fatty liver disease (NAFLD), now termed metabolic dysfunction-associated steatotic liver disease (MASLD). In parallel, she studied the interplay between endoplasmic reticulum (ER) stress-mediated unfolded protein response (UPR) signalling and autophagy, and examined how these processes are modulated by bioactive plant extracts in various cellular contexts.
She is particularly interested in exploring inter-organ communication, such as pancreas-liver crosstalk, and how these interactions influence systemic metabolism and contribute to the onset and progression of T2D, along with its complications. Her long-term research goal is to advance our understanding of the cellular and molecular mechanisms driving T2D and to identify novel therapeutic targets and strategies. -
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.
