UF BME is thrilled to welcome its newest addition to the faculty, Dr. Kuang Gong, who joins as an assistant professor this fall. Dr. Gong brings a wealth of knowledge and experience in medical imaging, deep learning, and data science, which is expected to significantly contribute to the advancement of research and education in the department.
Prior to joining UF BME, Dr. Gong served as an assistant professor in the Department of Radiology at Massachusetts General Hospital, Harvard Medical School, where he conducted research in the field of medical imaging. He obtained his M.S. degree in statistics and Ph.D. degree in biomedical engineering from the prestigious University of California at Davis. Furthermore, he pursued postdoctoral training in the Department of Radiology at Massachusetts General Hospital and Harvard Medical School, solidifying his expertise in the intersection of medicine and engineering.
Dr. Gong’s research interests are centered around the convergence of deep learning, medical imaging, and data science to enhance the diagnosis and treatment monitoring of various diseases, particularly Alzheimer’s disease (AD) and cancer. His work involves developing novel methodologies in medical physics-informed deep learning, leveraging prior information-guided network design, and applying clinical task-driven network training for more accurate and precise results.
During his academic career, Dr. Gong has an impressive track record of scholarly accomplishments, with 32 published journal papers and multiple research grants from the National Institutes of Health (NIH). He was also recognized with the prestigious Bruce H. Hasegawa Young Investigator Medical Imaging Science Award from the IEEE Nuclear and Plasma Sciences Society in 2021. This award acknowledges his outstanding contributions to machine learning-based PET image reconstruction, denoising, and attenuation correction, which have significant implications for the field of medical imaging.