Stanford University
Showing 24,101-24,150 of 36,308 Results
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Jee-Young Park
Korean Studies Librarian, East Asia Library
BioJee-Young Park is responsible for developing and maintaining the Korean Studies Collection and she provides reference services to support the research and teaching needs of the faculty and students at Stanford University. Prior to joining Stanford University, Jee-Young was a Korean Studies Librarian at the University of Chicago. She is a graduate of the San Jose State University School of Library and Information Science and the University of California, Berkeley, where she earned her Bachelor of Arts degree in Japanese Language and Culture.
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Jon Park, MD, FRCSC
Saunders Family Professor
Current Research and Scholarly InterestsNon-fusion dynamic spinal stabilization, artificial disc technologies, and regenerative spinal technologies.
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Joon Sung Park
Affiliate, Program-Bernstein, M.
BioJoon Sung Park is a computer science PhD student in the Human-Computer Interaction and Natural Language Processing groups at Stanford University. His work introduces the concept of, and the techniques for building generative agents -- computational software agents that simulate human behavior. His work has won best paper awards at UIST and CHI, as well as multiple best paper nominations and other paper awards at CHI, CSCW, and ASSETS, and has been reported in venues such as Nature, Science, NBC, The New York Times, The Times, and The Guardian. Joon is recognized with the Microsoft Research Ph.D. Fellowship (2022), Terry Winograd Fellowship (2021), and Siebel Scholar Award (2019).
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Jun Hyung Park
Research and Development Science and Engineer 1, Rad/Molecular Imaging Program at Stanford
Current Role at StanfordI joined in Cyclotron and radiochemstry facility in 2014. I focus on routine radiopharmaceutical production, including 18F tracers (18F-Flumazenil, 18F-FTC-146, 18F-FLT, 18F Arag, 18F-FSPG etc.); 11C tracers (11C UCB-J, 11C-raclopride, 11C-PIB, 11C-methionine, 11C DPA-713 etc.); 15O-H2O and 68Ga-DOTATATE radiochemistry for clinical use and supporting various of pre-clinical studies.
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Junyoung Park
Postdoctoral Scholar, Neurology and Neurological Sciences
BioDr. Jun Young graduated from the Department of Biostatistics at the School of Public Health, Seoul National University, Korea. His major field of study is biostatistics, with a specific focus on the application of machine learning and statistical analysis to medical imaging and genetic data. During his doctoral studies, he concentrated on two primary research areas. Firstly, he dedicated himself to the development of deep learning models for medical images, primarily centered on T1-MRI and cognitive function test images related to Alzheimer's Disease. Secondly, he engaged in extensive genome-wide association analyses of medical images associated with Alzheimer's Disease, using statistical algorithms to uncover novel insights into the genetic factors contributing to this complex condition. Currently, as a postdoctoral fellow at the Greicius Lab at Stanford, he aims to develop statistical methods to discover novel structural variants and model polygenetic risk scores using long-read sequencing data.
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KT Park MD MS
Adjunct Professor, Medicine - Med/Gastroenterology and Hepatology
BioPrior to joining Genentech in 2018, Dr. Park was Associate Professor at Stanford University School of Medicine, Co-Director of the IBD Center at Stanford Children’s Health, and an expert in Crohn’s disease and ulcerative colitis. Currently, he is the Global Head of Gastroenterology, Hepatology & Metabolism in Product Development at Genentech and Roche. Trained as a health economist, during his tenure in academia, Dr Park held research grants and funding support focused on the cost-effectiveness of biologic treatment strategies and novel non-invasive biomarkers for children and adults with IBD. He led national research registries at the Crohn’s & Colitis Foundation and scientific/clinical committees in numerous GI societies and physicians’ organizations. He received his BA in chemistry/biochemistry at Duke University, MD at University of Tennessee, and MSc in Health Economics/Policy at Stanford where he completed his clinical and postdoctoral trainings. He is Adjunct Professor of Medicine in the Division of Gastroenterology & Hepatology at Stanford University. At Genentech Roche, Dr. Park directs a team of clinical scientists and medical directors overseeing clinical phase drug development in gastroenterology, hepatology, and metabolism.
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Lesley Park
Senior Research Scientist, Epidemiology and Population Health
BioStanford Advancing Health Equity and Diversity (AHEaD)
ahead.stanford.edu
Founding Co-Director (2020-present)
Veterans Aging Cohort Study (VACS)
Executive Director (2022-present)
Cancer Core Co-Director (2016-present)
International Workshop on HIV and Hepatitis Observational Databases (IWHOD)
iwhod.org
Chair, Scientific Secretariat (2024-present)
Dr. Lesley Park is a co-founding director of the Stanford AHEaD summer research program for college students from underrepresented and historically excluded groups in the health sciences. She is also the Executive Director of the VACS consortium, an international collaboration of methodologists, clinicians, and trainees who utilize the rich and valuable data from the Veterans Health Administration to do impactful research. VACS has been at the forefront of research to understand aging with HIV to improve patient care, particularly with respect to alcohol and other substance use, physiologic frailty, and polypharmacy. In recent years, the VACS mission has expanded to encompass other foci, including genomic research and most recently COVID-19.
Within the VACS, Dr. Park oversees cancer and COVID-19 outcomes research in persons with HIV/AIDS (PWH). Her research experience has focused on the intersection of cancer and HIV, examining epidemiologic methods for cancer research, cancer incidence trends, and cancer (particularly hepatocellular carcinoma) prevention in PWH. Dr. Park is an experienced epidemiologist, skilled in "big data" observational research, survival analysis, and SAS programming. She teaches courses in computing, data management, and epidemiologic analysis methods. Her prior experience includes research at the Yale School of Medicine and at the Center for Biostatistics in AIDS Research (CBAR) at the Harvard School of Public Health.
The International Workshop on HIV and Hepatitis Observational Databases (IWHOD) is an established scientific forum for the appropriate application of real-world data to emerging issues in infectious disease. Dr. Park leads the IWHOD scientific committee of internationally reknowned experts in infectious disease and is responsible for administrative and scientific coordination of IWHOD.
Previously, Dr. Park was one of the leaders of the Stanford Center for Population Health Sciences (PHS). PHS aims to improve the health of populations by bringing together diverse disciplines and data to understand and address social, environmental, behavioral, and biological factors. She oversaw all of the educational and training initiatives at PHS and was one of the founding directors of the PHS Data Center and PHS Postdoctoral Fellowship program. -
Namu Park
Postdoctoral Scholar, Biomedical Informatics
BioDr. Park is a Postdoctoral Scholar at the Division of Computational Medicine at Stanford University, where he is co-advised by Dr. Tina Hernandez-Boussard and Dr. Yair Bannet. He received his PhD in Biomedical and Health Informatics from the University of Washington.
His research focuses on clinical natural language processing and large language models for healthcare. He develops clinically grounded information extraction methods and evaluation frameworks that reflect real-world clinical workflows. His work examines how large language models can be aligned with clinical reasoning and rigorously evaluated for safe and effective deployment in health systems.
Through interdisciplinary collaboration, Dr. Park aims to bridge advances in foundation models with measurable clinical impact, emphasizing reliability, transparency, and scalability in AI-driven healthcare applications.
