Yonggang Shi is a Professor of Neurology and Biomedical Engineering at the University of Southern California. His research focuses on neuroimaging techniques, particularly diffusion MRI harmonization, brain connectivity analysis, and applications in Alzheimer’s disease and retinal imaging. He leads the NICR Group, advancing methods for connectome imaging and disease biomarker development. His work integrates machine learning with medical imaging to address challenges like distortion correction in MRI and tau pathology visualization. Key areas include retinal vessel analysis for neurodegenerative disease prediction and cortical thickness changes post-vision restoration. Shi’s contributions span both technical innovations (e.g., fiber orientation modeling) and clinical applications (e.g., Alzheimer’s subtyping). Publications highlight advancements in tractography, neuroimaging harmonization, and retinal OCT angiography. His research underscores interdisciplinary approaches bridging engineering and clinical neuroscience.
