Stanford University
Showing 401-450 of 734 Results
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Priscilla Yeung
Instructor, Pathology
BioPriscilla Yeung, MD, PhD is an Instructor in the Department of Pathology. Her current research is focused on applying top-down mass spectrometry and cell-surface proteomics to discover improved biomarkers for monoclonal gammopathies and other disorders. She completed her clinical pathology residency at Stanford University, MD/PhD training in protein biophysics at Northwestern University, and undergraduate studies at University of Pennsylvania.
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Serena Yeung-Levy
Assistant Professor of Biomedical Data Science and, by courtesy, of Electrical Engineering and of Computer Science
BioDr. Serena Yeung-Levy is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. Her research focus is on developing artificial intelligence and machine learning algorithms to enable new capabilities in biomedicine and healthcare. She has extensive expertise in deep learning and computer vision, and has developed computer vision algorithms for analyzing diverse types of visual data ranging from video capture of human behavior, to medical images and cell microscopy images.
Dr. Yeung-Levy leads the Medical AI and Computer Vision Lab at Stanford. She is affiliated with the Stanford Artificial Intelligence Laboratory, the Clinical Excellence Research Center, and the Center for Artificial Intelligence in Medicine & Imaging. She is also a Chan Zuckerberg Biohub Investigator and has served on the NIH Advisory Committee to the Director Working Group on Artificial Intelligence. -
Maame Yaa A. B. Yiadom
Associate Professor of Emergency Medicine (Adult Clinical/Academic)
BioDr. Yiadom is an Associate Professor of Emergency Medicine at Stanford University, leader, and researcher with expertise in clinical operations, care delivery, and strategic care delivery re-engineering. Her leadership involves finding value-generating opportunities to use routinely collected clinical data to inform more precise decision-making in clinical care delivery. This work involves the study, strategic deployment, and iterative redesign of novel care delivery pathway including digital health and artificial intelligence.
Dr. Yiadom was first trained in health care policy in Princeton University’s School of Public and International Affairs. She subsequently worked as a healthcare industry management consultant here in New York City for CSC Global Health Solutions Group, and was the Dean’s Office Chief of Staff at Drexel Medical School in Philadelphia. She completed her medical education at Robert Wood Johnson Medical School, a Masters in Public Health (MPH) at Harvard with additional health policy training from Johns Hopkins. She subsequently did residency at Mass General and Brigham and Women’s Hospitals’ Harvard affiliated program, and completed a Masters of Science in Clinical Investigation (MSCI) at Vanderbilt University.
She is the Principal Investigator for the Stanford Emergency Care Health Services Research Data Coordinating Center (HSR-DCC). Her research focuses on applications of evidence-based medicine to optimize clinical operations to target patient pathophysiology for time-sensitive conditions. STEMI is her prototype disease. Her group's primary methodologies include clinical practice epidemiology, workflow variability analysis, and clinically applied artificial intelligence. Current work includes refining clinical process, using informatics to support evidence-based practice, and performance measurement to identify real-world care improvement opportunities. This research is supported by the National Heart Lung and Blood Institute (NHLBI), and ED Benchmarking Alliance. The lab website is: https://yiadom-hsrdcc.com
Dr. Yiadom is also the Founding Director of the Emergency Department Operations Study Group (EDOSG), and on the Board of Directors for the Emergency Department Benchmarking Alliance (EDBA). -
Chao Yin
Postdoctoral Scholar, Physics
BioChao Yin is a Q-FARM Bloch Fellow at Stanford University. He earned his B.Sc. in Physics from Peking University (2016–2020), and completed his Ph.D. in Physics at University of Colorado Boulder (2020–2025) under the supervision of Prof. Andrew Lucas. His research interests include quantum information, condensed matter theory, and mathematical physics.
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David Zhen Yin
Senior Research Scientist - Physical
BioDavid Zhen Yin is the co-founder and program director of Stanford Mineral-X, a research innovation hub on creating resilient mineral supply chains for energy transitions. He is also the principal scientist at Stanford Center for Earth Resources Forecasting. Since 2024, David has been serving on the US National Academies Committee on optimizing the USGS Mineral Resources Program.
David develops data-scientific approaches for prediction, uncertainty quantification, and decision-making in critical earth resources exploration and development. He has broad experience with complex projects involving academia and industry and has broad knowledge of the fields. His research delivered several key technologies transferred as in-house technologies in Chevron, Equinor, and KoBold. Over the past decade, his research developments have been implemented on various subjects, from Antarctica bed topography modeling, North Sea and Gulf of Mexico energy projects, and numerous critical mineral exploration projects across five continents.
Before joining Stanford, David was a Research Associate at the Edinburgh Time-Lapse Project in Scotland, leading a geophysical monitoring research project in collaboration with Equinor from 2016 to 2018. He was also a technology consultant at Equinor's Research Center in Bergen, Norway. Then, he was a Chevron CoRE Postdoctoral Fellow at Stanford from 2018 to 2021. He was the Co-PI of the Stanford-KoBold collaboration from 2020 to 2022 which led to a $192.5 million Series B fundraising.
David received his Ph.D. in Geosciences from Heriot-Watt University, Edinburgh, UK, in 2016. His research interests include data science for geosciences, geological uncertainty quantification, and decision-making under uncertainty. He has authored one book and tens of articles in peer-reviewed journals and international conferences. -
Eric Yin
Temp - Non-Exempt, Human and Planetary Health
BioEric is a MS student in the Epidemiology and Clinical Research Program working under the supervision of Dr. Ashley Styczynski and Dr. Stephen Luby. His thesis explores how natural ventilation can be used to reduce airborne disease transmission in LMIC hospitals and the cost effectiveness of these strategies. Eric is also a Stanford CARE Team Science Fellow, helping undergraduate students develop quantitative skills for applications in Asian precision medicine research.
Prior to graduate school, Eric received his undergraduate degree from the University of Toronto with a major in neuroscience and a double minor in statistics and computer science. His previous research endeavors have involved the exploration of novel MRI biomarkers for Alzheimer's Disease, the localization of hippocampal engram neurons, and the cognitive impacts of surgically induced menopause. -
Lei Yin
Graduate, Stanford Center for Professional Development
Biohttps://www.linkedin.com/in/yinlei2000/
