Stanford University
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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. -
Ludmila Yurina
Lecturer, Music
BioLudmila Yurina is a Ukrainian composer whose work spans a wide range of styles, instruments, and ensembles. She graduated from the Kyiv Music Institute as a pianist and earned her degree in composition from the Kyiv State P. I. Tchaikovsky Conservatory, where she also completed her postgraduate studies.From 1990 to 2025, Yurina served as Associate Professor in the Department of Composition at the National Music Academy of Ukraine, teaching composition, orchestration, symphonic score reading, and contemporary music. Her professional training includes workshops with distinguished European composers such as Helmuth Lachenmann and Wolfgang Rihm.Yurina has been a guest composer and lecturer at leading institutions worldwide, including the Rheinsberg Music Academy, the Staatliche Hochschule für Musik und Darstellende Kunst Stuttgart, Texas Christian University, the City University of New York, and Stanford University. Her music has been performed internationally throughout Europe, North America, and beyond, in collaboration with prominent ensembles and musicians.
Her works are published by Donemus and Furore Verlag, and she is a member of professional organizations including NACUSA and ASCAP. In recognition of her contributions to contemporary music and culture, Ludmila Yurina has received numerous honors, including the Lysenko National Award, the Kosenko Award, the Lyatoshynsky National Award, and Fulbright Scholarships.
https://yurina.ru.gg
https://soundcloud.com/ludmilayurina
https://youtube.com/user/monodia
