This research course will be based on lectures, research materials reading and projects. The lecture part includes: 1). introduction to graph model and graph measures, 2). graph deep learning methods, 3). neuroimaging data and data processing, 4). graph deep learning on neroimaging data analysis, disease predictions and other related research topics. The related reading materials will be assigned to students in class. The students should read, understand, and present the materials that they are assigned to read. Also, two discussion classes will be organized for research brain storm. A final project will be assigned to students to train their practical ability on this topic.