Rate My Professor Xiaohan Yu

Dr. Xiaohan Yu is a Lecturer in Artificial Intelligence in the School of Computing at Macquarie University, where he commenced his appointment in December 2023. Prior to this role, he served as a Research Fellow at the ARC Research Hub for Driving Farming Productivity and Disease Prevention at Griffith University, Australia, following the completion of his doctoral studies at the same institution. His research specializations encompass ultra-fine-grained visual categorization (Ultra-FGVC), smart farming, and automated crop cultivar identification, with a focus on advancing computer vision and artificial intelligence applications. Dr. Yu has established and propelled forward progress in Ultra-FGVC research. He has authored over 70 peer-reviewed publications, more than 30 of which are in CORE A*-ranked venues including ICCV, CVPR, ECCV, AAAI, IJCAI, ACM MM, IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, IEEE Transactions on Image Processing, Pattern Recognition, IEEE Transactions on Neural Networks and Learning Systems, and IEEE Transactions on Circuits and Systems for Video Technology. His Google Scholar profile reflects over 1,767 citations. Key publications include "Mix-ViT: mixing attentive vision transformer for ultra-fine-grained visual categorization" (Pattern Recognition, 2023, 97 citations), "CLE-ViT: contrastive learning encoded transformer for ultra-fine-grained visual categorization" (IJCAI, 2023), "Feature fusion vision transformer for fine-grained visual categorization" (BMVC, 2021, 249 citations), "Cor-GS: sparse-view 3D Gaussian splatting via co-regularization" (ECCV, 2024, 120 citations), "MaskCOV: a random mask covariance network for ultra-fine-grained visual categorization" (Pattern Recognition, 2021, 71 citations), and "A client–server based recognition system: non-contact single/multiple emotional and behavioral state assessment methods" (Computer Methods and Programs in Biomedicine, 2025, 65 citations).