Rate My Professor Chang Xu

Chang Xu is an ARC Future Fellow and Associate Professor in Machine Learning and Computer Vision at the School of Computer Science, Faculty of Engineering, University of Sydney. He received his PhD degree from Peking University. His research focuses on machine learning algorithms and their applications in computer vision, with over 100 publications in top journals and conferences. Key contributions include advancements in efficient neural networks, vision transformers, multi-view learning, and generative models. Notable publications are GhostNet: More Features from Cheap Operations (CVPR 2020), Pre-trained Image Processing Transformer (2021), A Survey on Multi-view Learning (2013), CMT: Convolutional Neural Networks Meet Vision Transformers (2022), and Octo: An Open-source Generalist Robot Policy (2024). Xu collaborates on interdisciplinary projects connecting generative AI with climate science, neuroscience, and medical imaging.

Throughout his career, Xu has earned prestigious awards, including the NSW Premier's Prize for Early Career Researcher of the Year in Physical Sciences (2023), ACM SIGMM Rising Star Award (2023), Vice-Chancellor’s Award for Outstanding Early Career Research from the University of Sydney (2022), Sydney Research Accelerator (SOAR) Prize (2022), and Faculty Dean's Award for Supervision of HDR Students and Mentoring (2023). He has received distinguished paper awards such as AAAI 2023, Best Student Paper at ICDM 2022, Best Paper Candidate at CVPR 2021, and IJCAI 2018. Xu serves as Area Chair for NeurIPS, ICML, ICLR, KDD, CVPR, and ACM MM; Senior PC Member for AAAI and IJCAI; and Associate Editor for IEEE TPAMI, TIP, TMM, and TMLR, earning the Outstanding Associate Editor Award from IEEE TMM (2022) and Top Ten Distinguished Senior PC Member at IJCAI (2017). Earlier honors include CAAI Doctoral Dissertation Award (2017) and IBM PhD Fellowship (2015).