School of Engineering
Showing 171-180 of 180 Results
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Chik Patrick Yue
Visiting Professor, Electrical Engineering
BioProf. Yue received the Master and PhD degrees in EE from Stanford in 1994 and 1998, respectively. He has been a professor for over two decades, and taught IC design classes and conduct research at HKUST (2010-now), UC Santa Barbara (2006-11), Carnegie Mellon (2003-06), Tsinghua (visiting 2016), and Stanford (visiting 1998 & 2025-now). He has supervised over 10 post-docs, 30 PhD and 10 MPhil students. He has published over 250 technical papers, holds over 25 patents and accumulated over 10000 citations. Together with his students and teachers, he has been awarded the IEEE VLSI Circuit Symposium Test of Time Award (2024), the IEEE Circuits and Systems Society Outstanding Young Author Award (2017), and the Guanghua Engineering Science and Technology Youth Award by the Chinese Academy of Engineering (2016), and the ISSCC Best Student Paper Award (2003). Over the years, he has cofounded a number of startups in both Silicon Valley and Hong Kong including Atheros Communications (1998), Jetcomm Technologies (2014), LiPHY Communications (2018), and High5 Semiconductor (2024) to commercialize technologies from academic to industry.
Prof. Yue is a Fellow of the IEEE and Optica, and a member of the ACM. He has a diverse research interests spanning from optical wireline and mmWave wireless SoC and SiP design, neural implant microsystems, 3D computer vision models, and power network management system. -
Chang M. Yun
Ph.D. Student in Chemical Engineering, admitted Autumn 2023
Current Research and Scholarly InterestsGenomics, Computational Biology, Deep Learning
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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.
