Stanford University
Showing 701-762 of 762 Results
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Kuang Xu
Associate Professor of Operations, Information and Technology at the Graduate School of Business and, by courtesy, of Electrical Engineering
BioKuang Xu is an Associate Professor of Operations, Information and Technology at Stanford Graduate School of Business, and Associate Professor by courtesy with the Electrical Engineering Department, Stanford University. Born in Suzhou, China, he received the B.S. degree in Electrical Engineering (2009) from the University of Illinois at Urbana-Champaign, and the Ph.D. degree in Electrical Engineering and Computer Science (2014) from the Massachusetts Institute of Technology.
His research primarily focuses on understanding fundamental properties and design principles of large-scale stochastic systems using tools from probability theory and optimization, with applications in queueing networks, healthcare, privacy and machine learning. He received First Place in the INFORMS George E. Nicholson Student Paper Competition (2011), the Best Paper Award, as well as the Kenneth C. Sevcik Outstanding Student Paper Award at ACM SIGMETRICS (2013), and the ACM SIGMETRICS Rising Star Research Award (2020). He currently serves as an Associate Editor for Operations Research and Management Science. -
Yoshihisa Yamamoto
Professor of Electrical Engineering and of Applied Physics, Emeritus
Current Research and Scholarly InterestsExperimental Quantum Optics, Semiconductor Physics, Quantum Information
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Jerry Yang
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
BioJerry A. Yang is a PhD student in electrical engineering at Stanford University. He received his BS in electrical engineering from the University of Texas at Austin and MA in Education from Stanford University. He currently works on strain engineering in two-dimensional materials in Prof. Eric Pop's lab. In addition, he works on equity issues in engineering education in Prof. Sheri Sheppard's Designing Education Lab. His research interests span novel materials, devices, and systems for next-generation computing, engineering education research methods, and critical theories in engineering education. He is a student member of the Institute for Electrical and Electronics Engineers (IEEE), Materials Research Society (MRS), and American Society of Engineering Education (ASEE).
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Kevin G Yang
Undergraduate, Electrical Engineering
BioHi! I’m Kevin Yang.
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Xiaoxuan Yang
Visiting Postdoc, Electrical Engineering
Affiliate, Program-Mitra, S.BioXiaoxuan Yang is a Visiting Postdoctoral Scholar in the Robust Systems Group at Stanford University and an Incoming Assistant Professor in the Electrical and Computer Engineering Department at the University of Virginia. She received her Ph.D. degree in Electrical and Computer Engineering at Duke University under the supervision of Dr. Hai Helen Li and Dr. Yiran Chen. She received the B.S. degree in Electrical Engineering from Tsinghua University and the M.S. degree in Electrical Engineering from the University of California, Los Angeles (UCLA). Her research interests include emerging nonvolatile memory technologies, robustness and reliability enhancement in processing-in-memory designs, and hardware accelerators for deep learning applications.
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Yifan Yang
Masters Student in Electrical Engineering, admitted Autumn 2022
BioTop student in Electrical Engineering. He makes excellent contributions to all research he has been part of, not to mention classes. He always has ideas that inspire us. For coursework, he actively thinks, posts interesting questions in discussions, and helps answer other students' questions. The faculties are amazed by his extra knowledge about the field he is obsessed with. The answer and solutions he gave always surprised us with their simplicity and feasibility.
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Yinyu Ye
Kwoh-Ting Li Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsMy current research interests include Continuous and Discrete Optimization, Algorithm Development and Analyses, Algorithmic Game/Market Theory and Mechanism-Design, Markov Decision Process and Reinforcement Learning, Dynamic/Online Optimization and Resource Allocation, and Stochastic and Robust Decision Making. These areas have been the unique and core disciplines of MS&E, and extended to new application areas in AI, Machine Learning, Data Science, and Business Analytics.
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Bill Yen
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioBill Yen is a Ph.D. student in the Department of Electrical Engineering at Stanford University working in the area of low-power Internet of Things (IoT) systems. He is an interdisciplinary maker and environmental scientist passionate about solving issues related to food, water, and energy using smart technologies.
Yen's experience in industry (General Motors, CNH Industrial) and academic research (Northwestern - soil-powered computing, Stanford - low-power wireless communication) cultivated his interest in designing self-powered computing devices that boost system efficiency while lowering the environmental impact of existing processes. His work has been featured by The Independent, MIT Technology Review China, Hackster.io, and more. He is also a recipient of the Stanford Graduate Fellowship in Science & Engineering. -
Serena Yeung-Levy
Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering
BioDr. Serena Yeung-Levy 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-Levy leads the Medical AI and Computer Vision Lab at Stanford. She is affiliated with the Stanford Artificial Intelligence Laboratory, the Clinical Excellence Research Center, and the Center for Artificial Intelligence in Medicine & Imaging. She is also a Chan Zuckerberg Biohub Investigator and has served on the NIH Advisory Committee to the Director Working Group on Artificial Intelligence. -
Jeffrey Yu
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioI am a first year EE Ph.D. student majoring at Stanford University. I received my M.S. degree in Electrical Engineering from Stanford University in 2023 and my B.S. degree in Computer Engineering from UC San Diego in 2021. I am interested in DNN quantization and digital accelerator design.
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Mohammad Asif Zaman
Postdoctoral Scholar, Electrical Engineering
Current Research and Scholarly InterestsMy research focuses on trapping and controlled manipulation of sub-micron sized particles. The work included modeling, fabrication and testing of chips that employ optical forces and/or dielectrophoretic forces to trap and transport nanoparticles. Our goal is to develop lab-on-a-chip systems for biomedical and chemical applications.
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Howard Zebker
Professor of Electrical Engineering and of Geophysics
Current Research and Scholarly InterestsResearch
My students and I study the surfaces of Earth and planets using radar remote sensing methods. Our specialization is interferometric radar, or InSAR. InSAR is a technique to measure mm-scale surface deformation at fine resolution over wide areas, and much of our work follows from applying this technique to the study of earthquakes, volcanoes, and human-induced subsidence. We also address global environmental problems by tracking the movement of ice in the polar regions. whose ice mass balance affects sea level rise and global climate. We participate in NASA space missions such as Cassini, in which we now are examining the largest moon of Saturn, Titan, to try and deduce its composition and evolution. Our work includes experimental observation and modeling the measurements to best understand processes affecting the Earth and solar system. We use data acquired by spaceborne satellites and by large, ground-based radar telescopes to support our research.
Teaching
I teach courses related to remote sensing methods and applications, and how these methods can be used to study the world around us. At the undergraduate level, these include introductory remote sensing uses of the full electromagnetic spectrum to characterize Earth and planetary surfaces and atmospheres, and methods of digital image processing. I also teach a freshman and sophomore seminar course on natural hazards. At the graduate level, the courses are more specialized, including the math and physics of two-dimensional imaging systems, plus detailed ourses on imaging radar systems for geophysical applications.
Professional Activities
InSAR Review Board, NASA Jet Propulsion Laboratory (2006-present); editorial board, IEEE Proceedings (2005-present); NRC Earth Science and Applications from Space Panel on Solid Earth Hazards, Resources, and Dynamics (2005-present); Chair, Western North America InSAR (WInSAR) Consortium (2004-06); organizing committee, NASA/NSF/USGS InSAR working group; International Union of Radioscience (URSI) Board of Experts for Medal Evaluations (2004-05); National Astronomy and Ionospheric Center, Arecibo Observatory, Visiting Committee, (2002-04; chair, 2003-04); NASA Alaska SAR Facility users working group (2000-present); associate editor, IEEE Transactions on Geoscience and Remote Sensing (1998-present); fellow, IEEE (1998) -
Xue Zhang
Masters Student in Electrical Engineering, admitted Autumn 2021
Bio2018 - Now
Software Engineer at Meta
2014 - 2018
B.S. in Computer Science
Washington University in St.Louis -
Orr Zohar
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
Masters Student in Computer Science, admitted Autumn 2023BioOrr Zohar, from Haifa, Israel, is pursuing a PhD in electrical engineering at Stanford School of Engineering. He graduated summa cum laude from the Technion with a bachelor's degree in chemical engineering and a master’s degree in electrical engineering. Orr aspires to research, develop, and translate novel machine learning methods into the open surgical domain for applications such as AI-assisted surgery and surgical skill evaluation. Currently, developing novel learning methods in open-world learning and action quality evaluation at MARVL, advised by Prof. Serena Yeung.
Before coming to Stanford, he was a machine learning and algorithms engineer at proteanTecs and a junior researcher at the Technion's LNBD, where he developed soft electronic platforms that can heal, detect damage, and serve as multifunctional electronic skins. During his undergraduate degree, Orr worked as a visiting undergraduate researcher at the de la Zerda group, Stanford University, where he developed OCT image processing algorithms for improved molecular contrast and depth-of-field. Orr is a Bazan Group scholar and was awarded the Sieden family prize for his contributions to YBCO-based photon detectors' development.
