Member

Dr. Gang Li is an Associate Professor with tenure in the Department of Radiology at the University of North Carolina at Chapel Hill. He received his PhD in 2010 from Northwestern Polytechnical University. He was a Research Fellow at The Methodist Hospital Research Institute, Weill Medical College of Cornell University (2007-2008) and Harvard Medical School (2005-2007). He is the recipient of the NIH K01 Career Award (2015-2019) and the Distinguished Investigator Award of the Academy for Radiology & Biomedical Imaging Research (2022).

Dr. Zhengwang Wu is a Research Instructor at the University of North Carolina at Chapel Hill. He got his PhD degree in pattern recognition and intelligent system from Xi’an Jiaotong University, China. His research focuses on computer vision, machine learning, pattern recognition methods, and their applications in medical image segmentation, classification and visualization. He is currently working on infant cortical surface atlas construction and computational pipeline development, as well as using state-of-the-art machine learning methods for infant MRI data analysis.

Dr. Liangjun Chen is a postdoctoral researcher at the University of North Carolina at Chapel Hill. He received his Ph.D. degree in computer science from Xi’an Jiaotong University, China. His research focuses on machine learning and its applications in medical image segmentation, classification, and visualization. He is currently working on using state-of-the-art machine learning methods for pediatric brain MR image processing.

Dr. Ya Wang is a postdoctoral researcher at the University of North Carolina at Chapel Hill. She received her M.D. in Human Anatomy from Southern Medical University, China. Her research focuses on the analysis of infant brain development and disease-related brain developmental abnormalities.

Dr. Fenqiang Zhao is a postdoctoral researcher at the University of North Carolina at Chapel Hill. He received his Ph.D. degree in biomedical engineering from Zhejiang University, China in 2021. He mainly works on surface mesh-based deep learning methods for analyzing cortical surface data, such as cortical surface parcellation, prediction, and registration.

Jiale Cheng is a master student at the School of Electronic and Information Engineering, South China University of Technology. His current research focuses on the development of deep learning-based methods for analyzing cortical surface data.

Xinrui Yuan is a Ph.D. Candidate at School of Biomedical Engineering, Southern Medical University. Her current research focuses on the analysis of cortical surface data.

Laifa Ma is a Ph.D. candidate at College of Computer Science and Electronic Engineering, Hunan University. He mainly works on fetal brain data analysis based on deep learning.