Guanglin Zhou

Dr. Guanglin Zhou is a Postdoctoral Research Fellow at the School of Electrical Engineering and Computer Science, part of the Faculty of Engineering, Architecture and Information Technology at The University of Queensland. He holds a Doctor of Philosophy in Electrical Engineering and Computer Science from the University of New South Wales. His research focuses on machine learning, causal inference, and domain adaptation, with applications in healthcare, recommendation systems, and computer vision.

Key research interests include developing counterfactual learning frameworks, enhancing model robustness through causal methods, and advancing domain generalization techniques. His work bridges causal theory with deep learning, particularly in generating clinically realistic data and improving foundation models' adaptability to distribution shifts.

Dr. Zhou's publications span topics like contrastive visual prompting for domain adaptation, cycle-balanced representation learning for causal inference, and deep reinforcement learning in recommender systems. He is available for supervision and has contributed to interdisciplinary projects combining knowledge graphs with spatio-temporal analysis for urban congestion prediction.