Stanford University
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Ying Cui
Postdoctoral Scholar, Biomedical Data Sciences
BioI am currently a postdoctoral scholar in the Department of Biomedical Data Science at Stanford Universiry. I received my Ph.D. in Biostatistics at Emory University. Prior to Emory, I received my B.S. in Statistics from Nankai University.
My research, located at the intersection of biomedical data science and statistics, is dedicated to enhancing the integration of statistical insights and data science innovations in biomedical research. I have a broad interest in developing innovative statistical methods and easy-to-use computational tools to understand complex associations using nonparametric and semiparametric methods, with recent work exploring their intersections with machine learning and causal inference to advance precision health. I have also been involved in various collaborative researches in multiple domains, including clinical trials and large language models (LLMs). -
Meysam Dadgar
Postdoctoral Scholar, Molecular Imaging Program at Stanford
BioMeysam Dadgar is a Postdoctoral Research Fellow at the Molecular Imaging Program at Stanford University, School of Medicine. He obtained his Ph.D. in Biophysics from Jagiellonian University in Kraków, Poland, as part of the J-PET collaboration, and previously held a Postdoctoral Fellowship at Ghent University, Belgium.
Dr. Dadgar’s research focuses on the development and optimization of next-generation positron emission tomography (PET) systems for cancer detection and precision medicine. His expertise spans PET instrumentation, Monte Carlo and GATE simulations, advanced image reconstruction, and AI-based image enhancement. He has made significant contributions to the design and evaluation of novel PET geometries, including dual-panel and total-body PET, as well as positronium imaging approaches that extend beyond conventional PET capabilities.
In addition to his PET-focused research, Dr. Dadgar gained unique experience at CERN, where he worked on advanced detector development, including trigger electronics, PET coincidence measurements, and composite material production under controlled conditions. These experiences provided him with a strong foundation in detector design, fabrication, and calibration that complements his biomedical imaging research.
He has authored more than 20 peer-reviewed publications, including papers in Science Advances, Nature Communications, IEEE Transactions on Radiation and Plasma Medical Sciences, and EJNMMI Physics. He has been recognized with multiple international fellowships and awards, including IEEE NSS/MIC Trainee Grants and national research grants in Europe.
At Stanford, Dr. Dadgar’s work integrates state-of-the-art medical imaging technologies, particle physics methods, and AI-driven modeling to improve sensitivity, resolution, and diagnostic accuracy in PET, with the ultimate goal of advancing early cancer detection and patient care.
