Chang Xu

Dr Chang Xu is Associate Professor in Machine Learning and Computer Vision at the School of Computer Science, University of Sydney. His research interests include computer vision, pattern recognition, deep learning, machine learning, audio processing, and artificial intelligence. His work focuses on areas such as multi-view learning, multi-label learning, visual search, and face recognition. His research outcomes have been widely published in prestigious journals and top tier conferences. He obtained a Bachelor of Engineering from Tianjin University, China, and a Ph.D. degree from Peking University, China. While pursuing his PhD degree, Chang received fellowships from IBM and Baidu.

Chang Xu is a researcher at the University of Sydney with expertise in Machine Learning, Computer Vision and Multimedia, and Data Mining. His work focuses on developing efficient and effective models for vision tasks, including image processing, multi-view learning, and neural architecture search. Xu has contributed to the design of lightweight neural networks, such as GhostNet and EfficientVMamba, and has explored techniques like knowledge distillation and data-free learning. His research also includes advancements in generative adversarial networks and semi-supervised learning methods. Xu's publications highlight his commitment to improving the efficiency and performance of machine learning models in various applications.