Stanford University
Showing 18,651-18,700 of 36,179 Results
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William Z Liu
Undergraduate, Computer Science
Undergraduate, MathematicsBioFrom 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. -
Y. Lucy Liu, MD, PhD
Senior Research Scientist, Pediatrics - Hematology/Oncology
Current Role at StanfordSenior Research Scientist
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Yan Liu
Staff Engineer, SLAC National Accelerator Laboratory
Current Role at StanfordStaff Engineer, SLAC National Accelerator Laboratory
CryoEM Specialist, Stanford-SLAC CryoEM Center -
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). -
Yusong Liu
Staff Scientist, SLAC National Accelerator Laboratory
BioI am currently an associate staff scientist in SLAC LCLS SRD Chemical Science Department. My research interest falls in excited state dynamics of small organic molecules, and I am particularly interested in using novel experimental techniques probing the ongoing dynamics in real time and space. The excited state dynamics in these systems usually take place in attoseconds to picoseconds time scales. The strongly-coupled electronic and nuclear dynamics often result in ultrafast energy redistribution as well as structure transformation, and facilitate many phenomenons in physics, chemistry, and biology.
My research builds on my extensive experience with ultrafast optical laser science and technology and time resolved spectroscopies. I am currently focusing on developing experiments utilizing multiple time-resolved spectroscopy or diffraction techniques probing molecular dynamics. These included time-resolved valence-ionization spectroscopy, Soft X-ray core-ionization spectroscopy, and ultrafast electron and hard X-ray diffraction. Most of my experiments are built upon the LCLS FEL X-ray beamline, MeV-UED facility in SLAC national lab, and our own tabletop ultrafast laser lab in Stanford PULSE institute. -
Zhuo Liu
Postdoctoral Scholar, Earth and Planetary Sciences
BioZhuo Liu is a postdoctoral scholar at the Stanford Doerr School of Sustainability, sponsored by Mineral-X. His expertise is in multi-geophysical data interpretation with both traditional methods and machine-learning-based methods for critical mineral exploration.
Zhuo Liu earned his PhD degree in Geophysics, with a minor degree in Geology, from the Colorado School of Mines (CSM), USA. His doctoral and postdoctoral research focused on advancing geophysical data interpretation methods and incorporating geologic prior information into the interpretation process in machine-learning and geostatistical approaches for mineral resources exploration.
Previously, Zhuo earned his Bachelor's degree in Applied Geophysics from the Central South University, China, and a Master's degree in Geophysics from the Colorado School of Mines (CSM), USA. He also visited the University of Science and Technology of China (USTC) as a Student Visiting Scholar under the mentorship of Dr. Xinming Wu in 2021. -
Zhuoyang Liu
Ph.D. Student in Business Administration, admitted Autumn 2020
Current Research and Scholarly InterestsI am broadly interested in decision-making under information and asymmetry for environmental conservation and healthcare operations applications. I study how people can optimally incentives land conservation using a combination of contract theory modeling and data-driven analytics. I bring together classic economic models with stochastic queueing control methods to provide novel insights on wholistic capacity planning for healthcare systems.
