Stanford University
Showing 1,851-1,900 of 2,493 Results
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Dr Kelvin Liu
Research Scientist, Center for Sustainable Development and Global Competitiveness
BioDr. Kelvin Liu is a Research Scientist at Stanford University. He holds a Ph.D. in Engineering from the University of Cambridge and completed his postdoctoral research at the University of Chinese Academy of Sciences. He also obtained dual master’s degrees from the University of Cambridge and Johns Hopkins University. Dr. Liu has previously served as an Industrial Associate at the Institute for Manufacturing, University of Cambridge. He has also served as a Partner Expert with the United Nations Industrial Development Organization (UNIDO), a lecturer in UNIDO’s Eco-Design Leadership Program.
Dr. Kelvin Liu has led and participated in over 15 major research projects funded by the European Union, the UK’s Engineering and Physical Sciences Research Council (EPSRC). His research spans artificial intelligence, technology innovation, strategic management, and industrial sustainability. He has published more than 20 papers in SCI/SSCI-indexed journals, holds three invention patents, serves as a reviewer for multiple international journals, and has delivered over 20 invited talks at international conferences and university seminars. -
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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William Z Liu
Masters Student in Computer Science, admitted Autumn 2025
BioFrom Bellevue, WA.
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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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Xinuo Liu
Affiliate, Archaeology
Visiting Scholar, ArchaeologyBioXinuo Liu is an Associate Professor in China and a Visiting Scholar in Archaeology at Stanford University. His research focuses on the archaeology of the Southern Silk Road, numismatics, and frontier governance in ancient China, with a comparative perspective across South Asia, Southeast Asia, Central Asia, and the Himalayan region. He bridges the fields of archaeology, cultural history, and heritage education, and is committed to making cultural knowledge accessible through museums and public engagement. Liu is a member of the International Council of Museums (ICOM), the American Numismatic Society (ANS), and the Chinese Society for the History of Sino-Foreign Relations.
He is the author of works on the Southern Silk Road and Chinese numismatics, and he seeks to foster cross-cultural dialogue through academic and public platforms. In addition to his scholarly work, he is actively engaged in social service, philanthropic initiatives, and alumni leadership networks, promoting the integration of cultural heritage with community development. -
Yan Liu
Cryo-Elect Micros Eng, Stanford Synchrotron Radiation Lightsource
Current Role at StanfordStaff Engineer, SLAC National Accelerator Laboratory
CryoEM Specialist, Stanford-SLAC CryoEM Center -
Yang Merik Liu
Instructor, Psychiatry and Behavioral Sciences
BioDr. Yang Merik Liu is currently an 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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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. His work has earned wide recognition, including the K99/R00 Award, the 2024 AJNR Lucien Levy Award, the David M. Yousem Research Fellow Award in both 2024 and 2025, and selection as a semi-finalist for the 2024 Cornelius G. Dyke Award. These honors underscore his promise as an investigator and his potential to make significant contributions to the field (https://med.stanford.edu/rsl/news/yongkai-liu-receives-research-fellow-award.html). His research has also been featured in Neurology Today, including his early work linking chain-of-thought methods with clinical reasoning to help advance the use of large language models in real-world clinical care (https://neurologytoday.aan.com/doi/10.1212/netod-blogs.10000031). -
Y. Lucy Liu, MD, PhD
Affiliate, Pediatrics - Hematology/Oncology
BioDr. Liu received her medical and clinical pharmacology training at two of the most prestigious medical institutions in China—West China School of Medicine (Sichuan University) and Peking Union Medical College (PUMC). She possesses extensive research experience in human molecular genetics, tumor biology, and experimental therapeutics.
Dr. Liu is internationally recognized for her expertise in two rare pediatric hematologic disorders: juvenile myelomonocytic leukemia (JMML) and Diamond-Blackfan anemia (DBA). She has authored more than 30 peer-reviewed publications in leading scientific journals, including Nature Genetics, Blood, Leukemia, and the Journal of Clinical Investigation (JCI). At her previous institutions, Dr. Liu served as a Principle Investigator (PI) and co-investigator on several NIH-funded research projects. In 2019, Dr. Liu joined the Department of Pediatrics at the Stanford University School of Medicine as a Senior Research Scientist. She recently developed a novel mouse model for DBA, which has proven to be a valuable tool for evaluating potential therapeutic strategies. Her current research focuses on elucidating the molecular pathogenesis of DBA and developing innovative treatment approaches for DBA. Since joining Stanford, Dr. Liu has published multiple manuscripts highlighting her ongoing research contributions. -
Yusong Liu
Staff Scientist, LCLS - Linac Coherent Light Source
BioI am a Staff Scientist in the LCLS Chemical Sciences Department at SLAC National Accelerator Laboratory. My research focuses on the excited-state dynamics of small organic molecules, with a particular emphasis on employing novel experimental techniques to probe these processes in real time and space.
Because these dynamics typically occur on attosecond to picosecond timescales, the strongly coupled electronic and nuclear motions drive ultrafast energy redistribution and structural transformations, processes that underpin fundamental phenomena across physics, chemistry, and biology.
Building on my extensive background in ultrafast laser science and time-resolved spectroscopy, my current work involves developing multi-modal experiments that integrate spectroscopy and diffraction. My toolkit includes time-resolved valence and soft X-ray core-ionization spectroscopy, as well as ultrafast electron and hard X-ray diffraction. These studies are conducted primarily at the LCLS X-ray FEL, the MeV-UED facility at SLAC, and our tabletop laser laboratories at the Stanford PULSE Institute.
