School of Medicine
Showing 751-800 of 1,580 Results
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Wen-yang Lin
Postdoctoral Scholar, Genetics
Current Research and Scholarly InterestsThe broad goal of my research interest is to identify intrinsic and extrinsic mediators of tumor growth and plasticity. My past research experiences will synergize with the expertise of Dr. Monte Winslow’s laboratory to allow the discovery of novel mechanisms of cancer progression. The integration of our molecular measurements with multiple types of ‘omics’ data will ultimately improve the diagnostic precision medicine.
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Yang Lin
Postdoctoral Scholar, Ophthalmology
BioYang Lin is a postdoctoral researcher in the laboratory of Dr. Andreas Tolias in the Department of Ophthalmology at Stanford University, where she joined in February 2024. She is also a member of the Enigma Project at Stanford.
Yang received her Ph.D. in 2023 from the IDG/McGovern Institute for Brain Research at Tsinghua University, where she trained under Dr. Song-Hai Shi. Her doctoral work focused on cortical development, investigating how developmental neuronal origin regulates neocortical map formation and characterizing the behavior and lineage progression of neural progenitors in the mammalian cortex.
As a postdoc, Yang has made a significant transition from developmental neuroscience into systems and computational neuroscience, focusing on how the visual brain supports active, goal-directed behavior. She currently leads behavioral and electrophysiological mice experiments in the Tolias lab. -
Lorraine Ling
Postdoctoral Scholar, Genetics
Current Research and Scholarly InterestsMy research focuses on the cell biology and biochemistry underlying the symbiotic relationship between corals and their partners, microscopic algae of the genus Symbiodinium. The algae live in the coral's gut tissue and provide its host products of photosynthesis while the coral provides inorganic carbon, nitrogen, and a safe habitat. I'm investigating the signaling pathways involved in 1) recognizing the correct algae partner 2) transfer of nutrients between the two.
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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. -
Lin Liu
Postdoctoral Scholar, Chemistry
BioI finished my undergraduate study in general chemistry at Shandong Normal University in 2014. Later, I continued to my master’s studies in organic chemistry at Lanzhou University. In 2018, I moved to Baylor University conducting research under the mentorship of Professor John L. Wood. During my graduate studies, I mainly focused on the total syntheses of natural products. In 2024, I joined the Khosla lab and Cui lab as a joint postdoc. Outside the lab, I like cooking, playing basketball, and watching movies
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Ruizhe Liu
Postdoctoral Scholar, Psychiatry
Bio2014 - 2020Graduate student, Department of Psychology, University of Pittsburgh, Pittsburgh, PA, U.S.
2009 - 2012 M.S. in Psychology. School of Psychology, Beijing Normal University (BNU), Beijing, China
2005 - 2009 B.S. in Psychology. Department of Psychology, East China Normal University (ECNU), Shanghai, China -
Sheng Liu
Postdoctoral Scholar, Biomedical Data Sciences
BioSheng Liu is a postdoctoral fellow at Stanford University. In May 2023, He received a Ph.D. degree from New York University, majoring in Data Science and Machine Learning. His background is in the area of robust and trustworthy machine learning, machine learning for healthcare.
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Yang Merik Liu
Postdoctoral Scholar, Psychiatry
BioDr. Yang Merik Liu is currently a postdoctoral scholar (and an incoming Instructor) with the Department of Psychiatry and Behavioral Sciences, Stanford University, and is affiliated with the Center for Machine Vision and Signal Analysis, University of Oulu, Finland. He is a Co-I of the NIH/NIA R33 Grant, and was a PI of the North Ostrobothnia Regional Fund of the Finnish Cultural Foundation and the Instrumentarium Science Foundation, carrying out research on digital measures with affective intelligence. Dr. Liu coordinated and managed "AI Forum" and "ICT 2023 TrustFace" projects during his postdoctoral research in University of Oulu since Jan. 2022, led by Academy Professor Guoying Zhao, member of Academia Europaea, member of the Finnish Academy of Sciences and Letters, IEEE/IAPR/ELLIS Fellow. He was also a former researcher with the Haaga-Helia University of Applied Sciences, in 2023, and was a visiting scholar with Hong Kong Baptist University (Prof. Pong Chi Yuen) and University of Cambridge (Prof. Hatice Gunes), in 2023 and 2024, respectively. Dr. Liu has published more than 40 papers in reputable journals and proceedings. He served as the Session Chair of IEEE FG 2025, the Track Chair of IEEE COINS 2026, the Guest Associate Editor of Frontiers in Psychology and Frontiers in Human Neurosciences, and organized tutorials and workshops in international conferences, i.e., HHAI 2024 and IEEE FG 2025. Dr. Liu was an Assistant Lecturer of the "Affective Computing" course in University of Oulu, in 2023. He mentored junior doctoral researchers and co-supervised post-/undergraduate students. His research interests include affective computing, cognitive computation for cross-species behavioral, and AI for aging medicine.
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Quentin Loisel
Postdoctoral Scholar, SCRDP/ Heart Disease Prevention
BioQuentin Loisel is a postdoctoral researcher at the Meta-Research Innovation Center at Stanford (METRICS), where his work focuses on how artificial intelligence is transforming scientific practice and how researchers can use AI to produce better, more robust, and more equitable science. His broader agenda is to help define a hybrid model of scientific inquiry that deliberately and transparently combines human judgment and artificial intelligence.
His research sits at the intersection of artificial intelligence, epistemology of science, and research systems. He studies how AI tools reshape knowledge production across the research lifecycle, from problem formulation and data analysis to writing, peer review, and governance, and examines the epistemic, methodological, and institutional consequences of human–AI collaboration in science. His work aims to move beyond risk-focused or purely technical perspectives by developing evidence-based, researcher-centric models for integrating AI into everyday scientific practice.
Before joining Stanford, he completed a Marie Skłodowska-Curie PhD on digital technologies for co-creation, combining cognitive science, collective intelligence, and participatory research. He has co-funded and is coordinating the Artificial Intelligence working group of the Marie Curie Alumni Association (MCAA), which is a researcher-driven community of practice on AI in research. He also advises a social company, called Health Cascade, on how to integrate AI in teams to solve complex societal problems.
