School of Medicine
Showing 6,601-6,650 of 12,916 Results
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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.
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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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Nancy Fang Liu
Clinical Assistant Professor, Medicine
BioNancy Liu is a hospitalist and clinical assistant professor in the Department of Hospital Medicine. She earned her medical degree at the University of Pennsylvania and completed her internal medicine residency training at Stanford Health Care, where she was awarded the Julian Wolfsohn Award for dedication to leadership, clinical practice, and teaching during residency. Her interests are in quality improvement, end of life care, and health equity for underserved populations.
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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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Wanlu Liu
Affiliate, Institute for Immunity, Transplantation, and Infection Operations
Visiting Scholar, Institute for Immunity, Transplantation, and Infection OperationsBioAcademic Appointments
- Associate Professor, Zhejiang University
- Visiting Scholar, Stanford University School of Medicine (Mark M. Davis Lab)
Professional Education
- Ph. D., UCLA, Molecular Biology/Bioinformatics (2018)
- B.Med., Zhejiang University School of Medicine (2013)
Selected Publications:
- Ruonan Tian#, Zhejian Yu#, Ziwei Xue, Lize Wu, Jiaxin Wu, Shuo Cai, Bing Gao, Bing He, Yu Zhao, Jianhua Yao, Linrong Lu, Wanlu Liu*; Evaluation of T cell receptor construction methods from scRNA-seq data, Genomics Proteomics & Bioinformatics, 2025, 22(6), qzae086
- Ziwei Xue#, Lize Wu#, Ruonan Tian, Bing Gao, Yu Zhao, Bing He, Di Sun, Bingkang Zhao, Yicheng Li, Kaixiang Zhu, Lie Wang, Jianhua Yao*, Wanlu Liu*, Linrong Lu*; Integrative Mapping of Human CD8+ T Cell in Inflammation and Cancer, Nature Methods, 2025, 22(2), 435-445
- Jian Zhang#, Ruonan Tian#, Jie Yuan#, Zhang Siwen, Zhexu Chi, Weiwei Yu, Qianzhou Yu, Zhen Wang, Sheng Chen, Mobai Li, Dehang Yang, Tianyi Hu, Qiqi Deng, Xiaoyang Lu, Xue Zhang, Jia Liu, Wanlu Liu*, Di Wang*; A two-front nutrient supply environment fuels small intestinal physiology through differential regulation of nutrient absorption and host defense, Cell, 2024, 187(22), 6251-6271.
- Yaqi Su, Zhejian Yu, Siqian Jin, Zhipeng Ai, Ruihong Yuan, Xinyi Chen, Ziwei Xue, Yixin Guo, Di Chen, Hongqing Liang, Zuozhu Liu, Wanlu Liu*; Comprehensive assessment of mRNA isoform detection methods for long-read sequencing data, Nature Communications, 2024, 15, 3972
- Yixin Guo, Ziwei Xue, Meiting Gong, Siqian Jin, Xindi Wu, Wanlu Liu*; CRISPR-TE: a web-based tool to generate single guide RNAs targeting transposable elements, Mobile DNA, 2024, 14(1), 3
- Xinyu Xiang#, Yu Tao#, Jonathan DiRusso, Fei-Man Hsu, Jinchun Zhang, Ziwei Xue, Julien Pontis, Didier Trono, Wanlu Liu*, Amander T. Clark*; Human reproduction is regulated by retrotransposons derived from ancient Hominidae-specific viral infections, Nature Communications, 2022
- Lize Wu#, Ziwei Xue#, Siqian Jin, Jinchun Zhang, Yixin Guo, Yadan Bai, Xuexiao Jin, Chaochen Wang, Lie Wang, Zuozhu Liu, James Q. Wang, Linrong Lu*, Wanlu Liu*; huARdb: human Antigen Receptor database for interactive clonotype-transcriptome analysis at the single-cell level, Nucleic Acids Research, 2021, gkab857
- Yixin Guo, Ziwei Xue, Ruihong Yuan, Jingyi Jessica Li, William A. Pastor, Wanlu Liu*; RAD: a web application to identify region associated differentially expressed genes, Bioinformatics, 2021, 37(17): 2741-2743. -
Wendy Liu, MD, PhD
Assistant Professor of Ophthalmology
Current Research and Scholarly InterestsDr. Liu's research interests include the role of mechanosensation in the eye as it relates to the pathophysiology of glaucoma, with the goal of finding new druggable targets in glaucoma treatment.
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Xin Liu
Basic Life Science Research Scientist, Genetics
BioXin Liu is a postdoctoral Research Scientist in the Department of Genetics at Stanford University. Xin holds a PhD in Chemistry from the University of Michigan, Ann Arbor. Her basic research interests include RNA and protein biochemistry, enzymology, cancer immunology, and autoimmune disease. She has published papers in several prestigious journals in the field of biochemistry, including Nature Communications, Journal of American Chemical Society, and Nucleic Acids Research. The highlight of her multidisciplinary research includes the development of high-throughput enzymatic methods to discover anti-microbial agents and to reveal mechanisms behind human mitochondrial diseases, as well as innovative applications of genome engineering and machine-learning to decode principles of RNA editing in human cells. Her current research focuses on the mechanistic study of innate immune pathways.
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Y. Lucy Liu, MD, PhD
Senior Research Scientist, Pediatrics - Hematology/Oncology
Current Role at StanfordSenior Research Scientist
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Yang M. 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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Yi Liu
Postdoctoral Scholar, General Surgery
BioDr. Liu is a postdoc fellow at Stanford University School of Medicine. She is also a Chinese board-certificated, fellowship-trained clinician with demonstrated clinical and research expertise in Critical Care Medicine and interdisciplinary studies of nanomedicine.
She received her residency and fellowship training (Emergency Medicine & Intensive Care Medicine) at Chongqing Medical University (China) and Pierre and Marie Curie University (Paris 6 Univ., Pitié-Salpêtrière Hospital, Paris, France). In addition to her MD degree, She undertook PhD training in nanomedicine for cancer/infectious disease early detection and to identify potential new treatments for severe infectious/cancer patients. Her postdoctoral training in nano-enabled therapeutic at Stanford has helped advance her knowledge of how nanotechnology improve the application of nanomedicine in early diagnosis of diseases. She has published numerous articles on a wide range of nanoplatforms-related topics. She has also received several academic and teaching awards related to clinical skills and research on molecular imaging. -
Yongkai Liu
Instructor, Radiology
BioDr. Yongkai Liu is an instructor in the Department of Radiology, Division of Neuroimaging and Neurointervention at Stanford University. His research focuses on developing and evaluating advanced techniques to improve treatment decision-making and prognostication in brain diseases—particularly stroke—using imaging and deep learning. Dr. Liu is a recipient of the prestigious K99/R00 award for his work on integrating large language models with imaging-based deep learning for stroke outcome prediction.
Prior to joining Stanford, Dr. Liu earned his Ph.D. in Physics and Biology in Medicine from UCLA under the mentorship of Prof. Kyung Sung. This rigorous training equipped him with a strong foundation in medicine, deep learning, and physics. His Ph.D. thesis, titled “Advancing Segmentation and Classification Methods in Magnetic Resonance Imaging via Artificial Intelligence,” focused on developing cutting-edge deep learning and machine learning techniques for MRI-based clinical applications. During his master’s studies, he conducted research on CT Virtual Colonoscopy under the guidance of Prof. Jerome Liang, an IEEE Fellow.
Dr. Liu has also made significant contributions to the academic community as a peer reviewer for leading journals, including The Lancet Digital Health, NPJ Digital Medicine, Medical Image Analysis, Medical Physics, Scientific Reports, British Journal of Radiology, BJR|Artificial Intelligence, Annals of Clinical and Translational Neurology, IEEE Transactions on Medical Imaging, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Radiation and Plasma Medical Sciences, IEEE Transactions on Biomedical Engineering, and IEEE Transactions on Neural Networks and Learning Systems.
Dr. Liu is an emerging leader in neuroimaging, stroke research, and artificial intelligence, earning widespread recognition for his work. His accolades include the K99/R00 Award, the AJNR Lucien Levy Award, the David M. Yousem Research Fellow Award, and being named a semi-finalist for the 2024 Cornelius G. Dyke Award, all of which underscore his potential to make significant contributions in the future (https://med.stanford.edu/rsl/news/yongkai-liu-receives-research-fellow-award.html).
