School of Medicine
Showing 11-20 of 24 Results
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Craig Levin
Professor of Radiology (Molecular Imaging Program at Stanford/Nuclear Medicine) and, by courtesy, of Physics, of Electrical Engineering and of Bioengineering
Current Research and Scholarly InterestsMolecular Imaging Instrumentation
Laboratory
Our research interests involve the development of novel instrumentation and software algorithms for in vivo imaging of cellular and molecular signatures of disease in humans and small laboratory animal subjects. -
Margaret Chin-Chin Lin
Clinical Associate Professor, Radiology
BioDr. Margaret Lin is a board certified radiologist with subspecialty training in thoracic and cardiovascular imaging. Dr. Lin specializes in diseases affecting the lungs and airways, including cancer, infection, and interstitial and inhalational lung diseases. Dr. Lin has a passion for resident education and development of curricula and new educational tools. She is the current Program Director for the Diagnostic Radiology Residency Program.
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Jafi Alyssa Lipson
Clinical Associate Professor, Radiology
Current Research and Scholarly InterestsDr. Lipson's research interests include breast density and breast cancer risk assessment; informatics applications in breast imaging; early breast cancer detection and extent of disease evaluation using contrast enhanced mammography, digital breast tomosynthesis, and high resolution breast MRI; novel blood and imaging biomarkers of breast cancer burden and neoadjuvant treatment response; and image-guided wireless localization techniques for breast surgery.
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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, 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).
