Hailin Wang, Ph.D., is a Postdoctoral researcher at the Department of Statistics and Data Science, The Chinese University of Hong Kong. He received his Ph.D. in Statistics from Xi’an Jiaotong University and previously obtained his M.S. and B.S. in Statistics from Southwest University. He was also a visiting Ph.D. student at the RIKEN Center for Advanced Intelligence Project, Japan. His research focuses on high-dimensional statistics, matrix and tensor analysis, nonconvex optimization, and statistical machine learning, with applications in computer vision, hyperspectral imaging, and intelligent transportation systems. He has published extensively in leading journals such as IEEE TPAMI, IEEE TNNLS, and IEEE TIP, with over 900 citations. His recent work includes nonconvex statistical estimation for low-rank and smooth data and unified theories for matrix and tensor recovery . Dr. Wang has received multiple awards, including the Xu Zongben Applied Mathematics Paper Award and Best Student Paper Award at the Asian Conference on AI Technology. He actively serves as a reviewer for top-tier journals and conferences, including TPAMI, TIP, NeurIPS, ICML, and ICLR.