Dr. Zhangkai Wu is a Postdoctoral Research Fellow in Artificial Intelligence at the School of Computing, Macquarie University. He received his PhD in Electrical and Information Engineering, with a strong foundation in statistical machine learning and probabilistic generative models. His research focuses on deep generative modeling, including variational autoencoders, diffusion and consistency models, and their extensions to multimodal, temporal, and structured data. He is particularly interested in trustworthy and robust machine learning, addressing challenges such as uncertainty quantification, fairness-aware generation, domain shift, and concept drift. His work spans both theoretical modeling—variational inference, alignment, and calibration—and practical applications in vision, audio, time series, and urban-scale data. Dr. Wu actively publishes in leading AI venues and collaborates with interdisciplinary partners across academia and industry to develop principled and deployable generative learning systems.