Jing Zhang

Dr. Jing Zhang is a Lecturer in the School of Computing at the Australian National University (ANU), within the ANU College of Systems & Society. Previously, he served as a Research Fellow at ANU (2021–2022) and earned his PhD in 2021 under the supervision of Nick Barnes. His academic journey includes a Master’s (2010) and Bachelor’s (2007) from Northwestern Polytechnical University.

Education:

• PhD, Australian National University, 2021 (Supervisor: Nick Barnes)
• Master’s Degree, Northwestern Polytechnical University, 2010
• Bachelor’s Degree, Northwestern Polytechnical University, 2007

Research Interests:

Jing Zhang’s research focuses on computer vision and machine learning, with a particular emphasis on generative AI. His work addresses challenges in image, video, and audio generation/editing; explainable model adaptation; out-of-distribution detection; and adversarial attacks/defenses. He explores techniques to enhance model robustness and generalization across diverse domains.

Awards & Recognition:

• CVPR 2020 Paper Award Nominee for “UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders”

Teaching & Supervision:

Jing Zhang teaches COMP8536: Advanced Topics in Computer Vision (Semester 2, 2024) and ENGN4528/6528: Computer Vision (Semester 1, 2025). He currently supervises 4 PhD students as their primary advisor, focusing on cutting-edge research in computer vision and AI.

Professional Contributions:

• Co-organizer of tutorials on salient object detection (ACCV 2019) and uncertainty estimation (ICCV 2021)
• Regular reviewer for top venues: CVPR, ICCV, ECCV, TPAMI, IJCV, and others

Research Groups:

While not explicitly stated, his work is likely affiliated with ANU’s computer vision research groups, focusing on generative AI and robust machine learning systems.