Stanford University
Showing 18,701-18,750 of 36,312 Results
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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). -
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.
