Daochang Liu

Daochang Liu is a Lecturer in the Department of Computer Science and Software Engineering at The University of Western Australia (UWA). He is affiliated with the School of Physics, Maths and Computing. His research focuses on advanced AI technologies including Computer Vision, Generative AI, and Healthcare Data Science. Liu’s work contributes to UN Sustainable Development Goals through innovations in clinical data analysis and accessibility solutions for visual impairments.

His research expertise includes diffusion models, image quality enhancement, and adversarial machine learning. Notable contributions include developing DiffAct++ for action segmentation and pioneering adversarial noise-based transfer learning to bridge data gaps in generative AI. He actively supervises Higher Degree by Research students and has published extensively in top-tier conferences like CVPR and IJCAI.

Liu’s work integrates theoretical advancements with practical applications, such as personalized image generation for color vision deficiency populations. His research bridges computational methods with real-world healthcare challenges, demonstrated through collaborations on clinical data analysis and semantic-level image synthesis improvements.