Stanford University
Showing 291-300 of 540 Results
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Ruijiang Li
Associate Professor of Radiation Oncology (Radiation Physics)
Current Research and Scholarly InterestsMy lab's research is focused on the development of imaging and molecular biomarkers to improve cancer detection, diagnosis, prognostication, and prediction of therapy response. Our ultimate goal is to translate these biomarkers into clinical practice to guide optimal management and therapeutic decisions for precision cancer medicine.
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Shanjun Li
Steven and Roberta Denning Global Sustainability Professor, Senior Fellow at the Freeman Spogli Institute for International Studies, at the Stanford Institute for Economic Policy Research, and at the Precourt Institute for Energy
BioShanjun Li is the Steven and Roberta Denning Global Sustainability Professor and a Senior Fellow at both the Freeman Spogli Institute for International Studies (FSI) and the Stanford Institute for Economic Policy Research (SIEPR). His research focuses on environmental and energy economics, urban and transportation economics, empirical industrial organization, and the Chinese economy. His recent work examines pressing sustainability challenges and the rapid rise of clean energy industries in China, exploring their global implications to inform evidence-based policymaking.
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Emily C. Liang, MD
Assistant Professor of Medicine (Blood and Marrow Transplantation & Cellular Therapy)
BioDr. Liang is an Assistant Professor in the Division of Blood and Marrow Transplantation & Cellular Therapy. She cares for patients with multiple myeloma and other plasma cell disorders receiving cellular therapies. She graduated from Stanford University with a BA in Human Biology and earned her MD from the David Geffen School of Medicine at UCLA. She completed internal medicine residency at Stanford University and hematology/oncology fellowship at the University of Washington and Fred Hutchinson Cancer Center.
Dr. Liang's research integrates clinical investigation, statistical modeling, and translational science to characterize, predict, and mitigate CAR T-cell therapy-associated toxicities and advance cellular therapies for multiple myeloma. Her work has been published in Blood, Blood Advances, Transplantation and Cellular Therapy, and Bone Marrow Transplantation and has been funded by the National Institutes of Health, Conquer Cancer, and Swim Across America. -
April Shichu Liang
Clinical Assistant Professor, Medicine
BioApril S. Liang, M.D., is a Board-Certified internist and Clinical Informaticist. She serves as Clinical Assistant Professor in the Stanford Division of Hospital Medicine as well as Medical Informatics Director. Dr. Liang holds a B.S.E. in Computer Science from Princeton University and an M.D. from UCSF School of Medicine. She completed Internal Medicine residency at UCSF and Clinical Informatics fellowship at Stanford. Dr. Liang’s informatics interests include the implementation of AI tools in healthcare and data-driven quality improvement. Her past work includes the integrating a machine learning-driven clinical decision support tool in the EHR targeting lab overutilization and measuring the impact of ambient AI scribes on clinician documentation time.
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David Liang, MD, PhD
Professor of Medicine (Cardiovascular) at the Stanford University Medical Center, Emeritus
BioStanford researchers are creating a micro-device that physicians could guide through the body to help diagnose and treat clogged arteries and other diseases. Tethered to the outside world by a thin wire, a tiny machine creeps through blood vessels, searching out deadly plaques and obliterating them with a zap of a laser. While a laser will come later, for now David Liang, MD, PhD, is focusing on a tiny eye that could give physicians an unprecedented view into blood vessels.
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Percy Liang
Professor of Computer Science and Senior Fellow at the Stanford Institute for Human-Centered AI
BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011) and the director of the Center for Research on Foundation Models (CRFM). He is currently focused on making foundation models (in particular, language models) more accessible through open-source and understandable through rigorous benchmarking. In the past, he has worked on many topics centered on machine learning and natural language processing, including robustness, interpretability, human interaction, learning theory, grounding, semantics, and reasoning. He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), a Microsoft Research Faculty Fellowship (2014), and paper awards at ACL, EMNLP, ICML, COLT, ISMIR, CHI, UIST, and RSS.
