معرفی
Kuang Gong is an Assistant Professor in the J. Crayton Pruitt Family Department of Biomedical Engineering at the University of Florida’s Herbert Wertheim College of Engineering. His research focuses on integrating deep learning, medical imaging, and data science to improve disease diagnosis and treatment monitoring, particularly in Alzheimer’s and cancer. He holds a Ph.D. in Biomedical Engineering from UC Davis (2018), an M.S. in Statistics (2015), and a B.E. in Information Science & Electrical Engineering from Zhejiang University (2011).
Dr. Gong’s work emphasizes medical physics-informed deep learning, prior information-guided network design, and clinical task-driven training. His lab develops novel methodologies in PET image reconstruction, denoising, and parametric imaging, leveraging diffusion models and transformer architectures. Notable contributions include anatomically guided PET reconstruction, attenuation correction for PET/MR systems, and AI-driven tumor segmentation in head-and-neck cancers.
His publications span over 50 peer-reviewed articles, with recent focus on 3D diffusion models, cross-modal image registration, and low-dose PET imaging techniques. He serves as Associate Editor for Medical Physics and IEEE Transactions on Radiation and Plasma Medical Sciences, and has received prestigious awards including the Bruce H. Hasegawa Young Investigator Award (2021).
Research activities include collaborations with clinical partners to translate AI tools into clinical workflows, with applications in tau PET imaging for neurodegenerative diseases, motion correction in longitudinal studies, and multi-center analysis of COVID-19 prognosis using CT and electronic health records.
