Electrical Engineering
Showing 1-22 of 22 Results
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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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Bill Yen
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioBill Yen is a Ph.D. candidate 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, Fast Company, 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 Electrical Engineering and of Computer Science
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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Sajung Yun, PhD, MBA
Visiting Scholar, Center for East Asian Studies
Affiliate, US-Asia Technology Management CenterBioDr. Sajung Yun is a multifaceted scholar and entrepreneur whose work bridges the disciplines of genomics, biomedical sciences, and artificial intelligence. At Stanford, his current research focuses on AI's self-recognition, self-protection, and self-perpetuation mechanisms and their implications in relation to Artificial General Intelligence and Super-Specialized Generalist Intelligence in medicine. He also serves as Adjunct Professor of Bioinformatics at Johns Hopkins University where he teaches bioinformatics courses over the last ten years.
Dr. Yun earned his Ph.D. in Biomedical Sciences from the John A. Burns School of Medicine and his MBA with concentrations in Healthcare Management and Entrepreneurship from Johns Hopkins University, blending rigorous scientific training with strategic leadership in medical innovation. He also attended M.D. program and completed 121 credits at John A. Burns School of Medicine. His academic appointments also include a concurrent role as Adjunct Professor in Biomedical Engineering at Ulsan National Institute of Science and Technology (UNIST), where he continues to contribute to global collaborations in AI-driven bioinformatics and healthcare system optimization.
As the Founder and CEO of Predictive AI, Dr. Yun leads a digital health company specializing in AI-based personalized preventive medicine platforms. Under his leadership, the company has been recognized for excellence in innovation, receiving distinctions such as the 2023 and 2022 4th Industrial Revolution Awards in AI and Biohealth, and the 2024 Venture Business Association President’s Award at the 6th Korea SME & Startup Awards. In recognition of his contributions to global innovation and leadership, Dr. Yun was named a 2025 Forbes Global CEO Delegate. In 2026, he lead his company to win Honoree Award in CES.
Dr. Yun’s professional career began as a Research Fellow at the U.S. National Institutes of Health (NIH), where he investigated advanced gene editing and genetic surgical methods. His research portfolio spans topics including next-generation sequencing data analysis, MRI volumetric analysis, and AI applications in biomedical imaging. His numerous publications and work continues to contribute to the evolving landscape of digital healthcare, emphasizing the convergence of data science, clinical insight, and artificial intelligence for human health advancement.
