Stanford University
Showing 6,351-6,400 of 6,605 Results
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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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Yaochun Yu
Assistant Professor of Civil and Environmental Engineering
BioMy research focuses on functional environmental microbiology and environmental analytical chemistry to uncover and harness microorganisms for chemical biotransformation. We integrate high-resolution mass spectrometry, meta-omics sequencing, molecular microbiology and biochemistry, and computational modeling to identify the functional microbes, genes, and enzymes that drive these processes. Building on these mechanistic insights, we aim to develop environmentally benign chemicals and novel biosolutions for bioremediation and waste-to-resource recovery.
I am also interested in how anthropogenic perturbations (i.e., chemical exposure) reshape microbial biodiversity and ecosystem function across natural and engineered ecosystems. We aim to resolve these cause–effect relationships and, using standardized and synthetic microbial communities, run comparable, hypothesis-driven experiments that translate fundamental insights into predictive tools and practical interventions. The aim is to help keep human activities within the safe operating space of planetary boundaries while advancing environmental and public health. -
Yigao Yuan
Postdoctoral Scholar, Materials Science and Engineering
Bioheterogeneous photocatalysis
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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.
