Assoc. Prof. Xun Jin
Yanbian University
Xun Jin received the Ph.D. degree from Sangmyung University, South Korea. He was a researcher at Creative Contents Labs of Sangmyung University. He is currently an Associate Professor in Department of Computer Science and Technology in Yanbian University, China. He is the director of Artificial Intelligence Teaching and Research Section of Yanbian University. He serves as a reviewer for several international journals such as Electronics, Mathematics and Engineering Applications of Artificial Intelligence. He has extensive research experience in the field of multimedia digital content security, including digital watermarking, plagiarism detection, and copyright protection for images, videos, texts, and other digital contents. In recent years, through the research on feature engineering-based copyright authentication technology, valuable achievements have been made in the detection of digital contents such as comics, 3D models, music, and games.
Speech Title: "Enhancing Digital Image Copyright Protection with Neural Network Models"
Dr. Xiangyang Ju
NHS Greater Glasgow and Clyde
Dr. Ju is a leading researcher in 3D shape capture, modelling, and medical image analysis with over 30 years of experience. He pioneered high-resolution 3D photogrammetry for live animal and human scanning, developing an innovative shape conformation method (EPSRC GR/M47676/01) to establish dense correspondence for morphometric analysis. This work became core IP for a spin-out company commercializing 3D imaging technologies. Under a BBSRC grant (17/D1534), he collaborated with Silsoe Research Institute to refine 3D conformation techniques, correlating livestock growth scans with genotype and diet to predict meat/fat yields. His research also advanced 3D facial expression transfer (RGU RDI 2006) and multi-view 3D photogrammetry integration, improving dynamic shape reconstruction. Currently, Dr. Ju applies 3D/4D imaging to oral/maxillofacial surgery planning, OCT for intravascular/retinal diagnostics, and PET/CT analysis for lung cancer. His interdisciplinary work bridges computer graphics, biomedical engineering, and clinical practice, addressing real-world challenges in healthcare and industry. With numerous peer-reviewed publications and collaborations, he drives innovation at the intersection of imaging technology and computational analysis.
Speech Title: "Assessment of The Expressions of Facial Paralysis Using PointNet: A Deep Learning Approach for 3D Facial Point Cloud Analysis"