Stanford University
Showing 441-450 of 670 Results
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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. -
Ugur Parlatan
Basic Life Research Scientist, Rad/Canary Center at Stanford for Cancer Early Detection
BioDr. Ugur Parlatan is a Basic Life Research Scientist at the Canary Center at Stanford for Cancer Early Detection. Trained as a physicist, he leads photonics laboratory activities and develops optical spectroscopy and imaging approaches for molecular fingerprinting and characterization of extracellular vesicles (EVs). His work includes designing and optimizing measurement workflows, analyzing EV signatures from biomedical samples, and supporting disease-focused studies across cancer and metabolic conditions (including lung cancer, glioblastoma, pancreatic cancer, diabetes, and hepatotoxicity). He also mentors trainees (including NIH CREST program interns) and contributes to manuscripts and grant applications.
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Magdalini Paschali
Postdoctoral Scholar, Radiology
Current Research and Scholarly InterestsMy research focuses on utilizing machine learning models to enhance the understanding, diagnosis, and treatment of clinical disorders. I am interested in multi-modal learning, combining imaging data like MRI and CT scans with non-imaging data such as electronic health records, creating more holistic and accurate diagnostic models. I am also interested in the robustness of deep neural networks under domain shifts, investigating how models perform when faced with changes in input data distributions.
Finally, I am interested in early biomarker identification using AI model interpretability, to enable the early detection and targeted treatment of chronic disorders. -
Anjali Patni
Postdoctoral Scholar, Radiology
BioPostdoctoral Scholar in the Department of Radiology (SUMIT Lab), working on precision drug delivery and minimally invasive therapy. Ph.D. in Oral Health Sciences from the University of Washington, with a research background spanning stem cell-derived tissue engineering, biomineralization, and regenerative medicine.
