Gang Li

Gang Li, PhD, is an Associate Professor in the Department of Radiology at the University of North Carolina School of Medicine, affiliated with the UNC IDEA Group (BRIC). His research focuses on advancing computational methods for neuroimaging analysis, particularly in infant and pediatric brain development. He holds a PhD from Northwestern Polytechnical University (Xi’an, China) and completed research fellowships at Weill Medical College of Cornell University and The Methodist Hospital Research Institute.

Dr. Li’s work integrates machine learning, artificial intelligence, and medical imaging to study brain development trajectories, functional connectivity, and the impact of environmental factors. His lab develops innovative algorithms for brain MRI analysis, including cortical surface reconstruction, functional connectivity prediction, and automated segmentation. Recent studies address topics such as prenatal phthalate exposure effects, maternal obesity influences on neonatal brain structure, and longitudinal cortical morphological changes in infants.

Publications highlight his expertise in federated learning for limited-data scenarios, deep learning applications in fetal brain imaging, and the creation of 4D infant brain atlases. His work emphasizes translational research, aiming to improve early diagnosis of neurodevelopmental disorders and enhance clinical decision-making through advanced imaging analytics.

Though no specific awards are listed, his extensive contributions to neuroimaging methodology and infant brain research reflect a high-impact academic profile. He advises students on cutting-edge projects at the intersection of AI and medical imaging, with a focus on reproducible and scalable solutions for neuroimaging challenges.