Stanford University
Showing 23,261-23,280 of 35,010 Results
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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 Stanford Cyclotron and Radiochemistry Facility in 2014. I focus on routine radiopharmaceutical production, development, optimization for clinical use and supporting various of pre-clinical studies.
18F tracers; 18F-Flumazenil, 18F-FTC-146, 18F-FLT, 18F MISO, 18F AraG, 18F-FSPG etc.
11C tracers; 11C UCB-J, 11C-raclopride, 11C-PIB, 11C-methionine, 11C DPA-713, 11C MGX10, 11, 11C-CN radiochemistry platform development
15O tracers; 15O-H2O, 15O gas Inhalation study
68Ga tracers; 68Ga-DOTATATE, 68Ga-PSMA
Quality Controls; HPLC, GC, TCD GC etc. -
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.
