School of Engineering
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Professor of Electrical Engineering and of Applied Physics, Emeritus
Current Research and Scholarly InterestsExperimental Quantum Optics, Semiconductor Physics, Quantum Information
Assistant Professor of Psychology and of Computer Science
Current Research and Scholarly InterestsOur lab's research lies at intersection of neuroscience, artificial intelligence, psychology and large-scale data analysis. It is founded on two mutually reinforcing hypotheses:
H1. By studying how the brain solves computational challenges, we can learn to build better artificial intelligence algorithms.
H2. Through improving artificial intelligence algorithms, we'll discover better models of how the brain works.
We investigate these hypotheses using techniques from computational modeling and artificial intelligence, high-throughput neurophysiology, functional brain imaging, behavioral psychophysics, and large-scale data analysis.
Associate Professor of Orthopaedic Surgery and of Bioengineering
Current Research and Scholarly InterestsOur research seeks to understand how microenvironmental cues regulate stem cell fate, and to develop novel biomaterials and stem cell-based therapeutics for tissue engineering and regenerative medicine. Our work spans from fundamental science, technology development, to translational research.We are particularly interested in developing better therapies for treating musculoskeletal diseases, cardiovascular diseases and cancer.
Yunzhi Peter Yang
Associate Professor of Orthopaedic Surgery and, by courtesy, of Materials Science and Engineering and of Bioengineering
Current Research and Scholarly InterestsYang lab's research interests are in the areas of bio-inspired biomaterials, medical devices, and 3D printing approaches for re-creating a suitable microenvironment for cell growth and tissue regeneration for musculoskeletal disease diagnosis and treatment, including multiple tissue healing such as rotator cuff injury, orthopedic diseases such as osteoporosis and osteonecrosis, and orthopedic traumas such as massive bone and muscle injuries.
Kwoh-Ting Li Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
BioYinyu Ye is currently the Kwoh-Ting Li Professor in the School of Engineering at the Department of Management Science and Engineering and Institute of Computational and Mathematical Engineering and the Director of the MS&E Industrial Affiliates Program, Stanford University. He received the B.S. degree in System Engineering from the Huazhong University of Science and Technology, China, and the M.S. and Ph.D. degrees in Engineering-Economic Systems and Operations Research from Stanford University. Ye's research interests lie in the areas of optimization, complexity theory, algorithm design and analysis, and applications of mathematical programming, operations research and system engineering. He is also interested in developing optimization software for various real-world applications. Current research topics include Liner Programming Algorithms, Markov Decision Processes, Computational Game/Market Equilibrium, Metric Distance Geometry, Dynamic Resource Allocation, and Stochastic and Robust Decision Making, etc. He is an INFORMS (The Institute for Operations Research and The Management Science) Fellow, and has received several research awards including the winner of the 2014 SIAG/Optimization Prize awarded every three years to the author(s) of the most outstanding paper, the inaugural 2012 ISMP Tseng Lectureship Prize for outstanding contribution to continuous optimization, the 2009 John von Neumann Theory Prize for fundamental sustained contributions to theory in Operations Research and the Management Sciences, the inaugural 2006 Farkas prize on Optimization, and the 2009 IBM Faculty Award. He has supervised numerous doctoral students at Stanford who received received the 2015 and 2013 Second Prize of INFORMS Nicholson Student Paper Competition, the 2013 INFORMS Computing Society Prize, the 2008 Nicholson Prize, and the 2006 and 2010 INFORMS Optimization Prizes for Young Researchers. Ye teaches courses on Optimization, Network and Integer Programming, Semidefinite Programming, etc. He has written extensively on Interior-Point Methods, Approximation Algorithms, Conic Optimization, and their applications; and served as a consultant or technical board member to a variety of industries, including MOSEK.
Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering
BioDr. Serena Yeung 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 leads the Medical AI and Computer Vision Lab at Stanford. She is affiliated with the Stanford Artificial Intelligence Laboratory, the Clinical Excellence Research Center, the Center for Artificial Intelligence in Medicine & Imaging, the Center for Human-Centered Artificial Intelligence, and Bio-X. She also serves on the NIH Advisory Committee to the Director Working Group on Artificial Intelligence.