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Doctor Junda Lu

 https://orcid.org/0009-0004-5450-0809

Accepting HDR Candidates

20212026

Research activity per year

Personal profile

Biography

Dr Junda Lu is an Associate Lecturer with the School of Computer, Data and Mathematical Sciences, Western Sydney University (WSU), and a member of WSU Artificial Intelligence Research Group (AIRG). He joined WSU in 2025.

He has previously worked at Amazon, CSIRO, Victoria University (Sydney), and Macquarie University. His research expertise includes Generative AI, Adversarial Machine Learning, and Information Retrieval.

He received his PhD degree in 2022 from the School of Computer Science and Engineering, University of New South Wales (UNSW), Australia. He obtained two Master's Degrees from University College Dublin (UCD), Ireland and Beijing University of Technology (BJUT), China.

Dr Lu brings a wealth of experience in research, teaching, and industry. 

  • As a researcher, he received the Best Paper Award from ACM ICMR.
  • As a lecturer, he received the Teaching Excellence Award from Victoria University Sydney.
  • As a student, he received First Class Honour, Excellent Postgraduate Student Award, and First Prize in the Computer Games Tournament.

 

He is currently working on Generative AI, especially in the Image Inpainting direction by using diffusion models. He is looking for HDR students who are interested in Generative AI, Adversarial Machine Learning, or Computer Vision. Dr Junda Lu is excited to deliver his knowledge within research and industry to his students. If you are interested, please feel free to contact him via [email protected].

 

PhD scholarship supported by the CSC is abaliable now
https://www.westernsydney.edu.au/schools/grs/scholarships/china-scholarship-council-research-scholarships

Related links

Qualifications

Doctor of Philosophy, University of New South Wales

Research keywords

  • Generative AI
  • Adversarial Machine Learning
  • Image Retrieval
  • Security

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Collaborations and top research areas from the last five years

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  • UNet-Twice: a simple structured reference-based inpainting framework

    Lu, J., Xu, Z., Wu, H., Cui, W., Huang, B., Chen, M. & Li, B., 2026, Computer Vision: ECCV 2026, 19th European Conference, Malmö, Sweden, September 8–12, 2026, Proceedings, Part LV. Favaro, P., Kukelova, Z., Maki, A., Rohrbach, A., Schindler, K. & Tombari, F. (eds.). Switzerland: Springer, p. 378-396 19 p. (Lecture Notes in Computer Science; vol. 17055).

    Research output: Chapter in Book / Conference Paper › Chapter › peer-review

  • WiTTA-Bench: Benchmarking Test-Time Adaptation for WiFi Sensing

    Li, B., Wang, Q., Lu, J., Zhang, L., Liu, Y., Zhu, C. & Cui, W., 2026, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

    Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

  • On adversarial training with incorrect labels

    Zhao, B. Z. H., Lu, J., Zhou, X., Vatsalan, D., Ikram, M. & Kaafar, M. A., 2025, Web Information Systems Engineering, WISE 2024: 25th International Conference, Doha, Qatar, December 2-5, 2024, Proceedings, Part IV. Barhamgi, M., Wang, H. & Wang, X. (eds.). Singapore: Springer, p. 116-132 17 p. (Lecture Notes in Computer Science; vol. 15439).

    Research output: Chapter in Book / Conference Paper › Chapter › peer-review

  • Boosting accuracy and robustness of student models via adaptive adversarial distillation

    Huang, B., Chen, M., Wang, Y., Lu, J., Cheng, M. & Wang, W., 2023, Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, 18 - 22 June 2023. U.S.: IEEE, p. 24668-24677 10 p.

    Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

    77 Citations (Scopus)

  • Distance maximization and defences on deep hashing based image retrieval

    Lu, J., Miao, Y., Chen, M., Huang, B., Li, B., Wang, W., Vatsalan, D. & Kaafar, M. A., 2023, Proceedings of the IEEE International Conference on Knowledge Graph (ICKG), 1-2 December 2023, Shanghai, China. Sheng, V. S., Hicks, C., Ling, C., Raghavan, V. & Wu, X. (eds.). U.S.: IEEE, p. 176-183 8 p.

    Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

View all 9 research outputs