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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 for brain diseases, particularly strokes, using imaging and deep learning. Liu's work is recognized for integrating large language models with imaging-based deep learning for stroke outcome prediction. He earned his Ph.D. in Physics, Biology, and Medicine from UCLA under the mentorship of Prof. Kyung Sung, where he focused on cutting-edge deep learning and machine learning techniques for MRI-based clinical applications. His master's studies included research on CT Virtual Colonoscopy. Liu has contributed significantly to the academic community as a peer reviewer for leading journals such as Lancet Digital Health and Medical Image Analysis. Acknowledged as an emerging leader in neuroimaging and stroke research, he has received several prestigious awards, including the K99/R00 award and the AJNR Lucien Levy Award, reflecting his potential to make significant contributions in the future.
The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.