About Me

Here is Chunyang Zhang (Cedric, 张春阳).

Chunyang Zhang completed his Bachelor’s degree in Weapon Science and Technology from Beijing Institute of Technology, Beijing, China, in 2020. He further pursued his Master’s degree in Control Science and Engineering from Beihang University, Beijing, China, graduating in 2023. Currently, I am conducting research on diffusion probabilistic models, advanced machine learning algorithms, and modern optimization techniques for my Ph.D. in Computer Science under the supervision of Prof. Dr. Daoyi Dong and Dr. Huadong Mo at the School of System and Computing, University of New South Wales.

If you’re interested in collaborating or discussing any aspect of my work, please feel free to email me at
chunyang[dot]zhang[at]unsw[dot]edu[dot]au

Academic Background

[Highlight] I am seeking Ph.D. students who share similar research interests as me. If you are interested in potential collaboration, kindly reach out to me!

• January, 2024 - Present: Ph.D. Student in Computer Science
  • School of System and Computing
  • University of New South Wales, Canberra, Australia
• September, 2020 - June, 2023: Master of Engineering in Control Science and Engineering
  • School of Automation Science and Electrical Engineering
  • Beihang University, Beijing, China
• August, 2016 - June, 2020: Bachelor of Science in Weapon Science and Technology
  • School of Mechatronics Engineering
  • Beijing Institute of Technology, Beijing, China

Research Interests

• Diffusion Probabilistic Model
• Deep Learning based Anomaly Detection
• Physics Informed Machine Learning
• Distributed Optimization
• Safe Reinforcement Learning
• Intelligent Control Theory

I am currently engaged in research that centers around diffusion probabilistic models and deep learning-based anomaly detection across diverse data types such as tabular, time series, graph network, image, and video. Additionally, I am exploring the development of deep safe reinforcement learning algorithms to ensure robust operation in various real-world applications. Furthermore, I am investigating distributed optimization techniques to tackle large-scale and complex practical problems. In essence, my goal is to leverage advanced machine learning technologies and modern optimization algorithms to expedite the deployment and enhancement of modern intricate scenarios.

News and Updates

• May, 2024：[Stepping Forward!] I earned the Certificate of Completion with Merit from the Graduate Teaching Training Program at UNSW.🥳🥳🥳!!!

• February, 2024：[New Journey!] I enrolled in the doctoral program in Computer Science at UNSW.💐😝💐!!!

• August, 2023：[Exciting News!] My research paper, “Robust Control of Multi-Line Re-Entrant Manufacturing Plants via Stochastic Continuum Models,” has been published by IEEE Transactions on Automation Science and Engineering. It’s my first Trans in the past four years. Thanks for all my co-authors and valuable contributors🚀🎉🎉🚀!!!