Personal profile
Biography
My research involves both theoretical and practical aspects. More specifically, this focuses on deep generative models, kernel methods, optimization in machine learning and Bayesian inference whose gained theories can be applied to supervised learning, semi-supervised learning, adversarial learning, online learning, anomaly detection, and cyber security. I have published in the top-notch conferences and high quality journals in machine learning, artificial intelligence, and data mining including NIPS, ICLR, AISTATS, UAI, IJCAI, ICDM and Journal of Machine Learning Research (JMLR).
Education/Academic qualification
Computer Science, Doctor of Philosophy, University of Canberra
Award Date: 27 Mar 2013
Research area keywords
- Deep Generative Models
- Optimisation for Machine Learning
- Kernel Methods
- Online Learning
- Deep Learning for Cyber Security
- Anomaly Detection
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being
Collaborations and top research areas from the last five years
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Generalizing Model Adaptation with Geometry: Applications in Model Fine-tuning, Editing, and Personalized AI
Le, T. (Primary Chief Investigator (PCI)) & Tafazzoli Harandi, M. (Chief Investigator (CI))
15/06/25 → 14/06/27
Project: Research
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Can Machines Unlearn? : Can Machines Unlearn? Toward Next-Generation Safe Artificial Intelligence
Phung, D. (Primary Chief Investigator (PCI)), Tafazzoli Harandi, M. (Chief Investigator (CI)), Le, T. (Chief Investigator (CI)), Zhang, J. (Chief Investigator (CI)) & Cai, J. (Chief Investigator (CI))
ARC - Australian Research Council
30/05/25 → 29/05/29
Project: Research
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TMLGenAI: Trustworthy Generative AI: Towards Safe and Aligned Foundation Models
Phung, D. (Primary Chief Investigator (PCI)), Vu, T. (Chief Investigator (CI)), Qu, L. (Chief Investigator (CI)), Le, T. (Chief Investigator (CI)), Haffari, R. (Chief Investigator (CI)), Webb, G. (Chief Investigator (CI)), Nicholson, A. (Chief Investigator (CI)), Ke, Q. (Chief Investigator (CI)), Cai, J. (Chief Investigator (CI)) & Bui, T. (Chief Investigator (CI))
11/06/24 → 30/06/26
Project: Research
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Robust Machine Learning: Data Efficient and Geometric Optimal Transport for Robust Machine Learning
Le, T. (Primary Chief Investigator (PCI)), Phung, D. (Chief Investigator (CI)), Pham, T. D. (Chief Investigator (CI)), Tran, T. (Chief Investigator (CI)) & Bui, H. (Chief Investigator (CI))
30/09/23 → 29/09/26
Project: Research
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Exploiting Geometries of Learning for Fast, Adaptive and Robust AI
Phung, D. (Primary Chief Investigator (PCI)), Tafazzoli Harandi, M. (Chief Investigator (CI)), Hartley, R. I. (Chief Investigator (CI)), Le, T. (Chief Investigator (CI)) & Koniusz, P. (Partner Investigator (PI))
ARC - Australian Research Council
8/05/23 → 7/05/27
Project: Research
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PromptDSI: Prompt-Based Rehearsal-Free Continual Learning for Document Retrieval
Huynh, T. L., Vu, T. T., Wang, W., Wei, Y., Le, T., Gasevic, D., Li, Y. F. & Do, T. T., 2026, Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025 Porto, Portugal, September 15–19, 2025 Proceedings, Part VII. Ribeiro, R. P., Soares, C., Gama, J., Pfahringer, B., Japkowicz, N., Larrañaga, P., Jorge, A. M. & Abreu, P. H. (eds.). Cham Switzerland: Springer, p. 383-401 19 p. (Lecture Notes in Computer Science; vol. 16019 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
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DiffAugment: Diffusion Based Long-Tailed Visual Relationship Recognition
Gupta, P., Nguyen, T., Dhall, A., Hayat, M., Le, T. & Do, T. T., 2025, Computer Vision – ECCV 2024 Workshops - Milan, Italy, September 29–October 4, 2024 Proceedings, Part XX. Del Bue, A., Canton, C., Pont-Tuset, J. & Tommasi, T. (eds.). Cham Switzerland: Springer, p. 36-52 17 p. (Lecture Notes in Computer Science; vol. 15642).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
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Enhancing Dataset Distillation via Non-Critical Region Refinement
Tran, M. T., Le, T., Le, X. M., Do, T. T. & Phung, D., 2025, Proceedings, 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2025. Mortensen, E. (ed.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 10015-10024 10 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
1 Link opens in a new tab Citation (Scopus) -
Fantastic Targets for Concept Erasure in Diffusion Models and Where to Find Them
Bui, A., Vu, T. T., Vuong, L., Le, T., Montague, P., Abraham, T., Kim, J. & Phung, D., 2025, 13th International Conference on Learning Representations, ICLR 2025. Yue, Y., Garg, A., Peng, N., Sha, F. & Yu, R. (eds.). Appleton WI USA: International Conference on Learning Representations (ICLR), p. 84305-84347 43 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access -
HVQ-VAE: Variational auto-encoder with hyperbolic vector quantization
Chen, S., Fang, P., Harandi, M., Le, T., Cai, J. & Phung, D., Jul 2025, In: Computer Vision and Image Understanding. 258, 10 p., 104392.Research output: Contribution to journal › Article › Research › peer-review
1 Link opens in a new tab Citation (Scopus)
Prizes
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The best student paper award at KDD 2023
Le, T. (Recipient), 20 Sept 2023
Prize: Prize (including medals and awards)
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The first prize of Imagine Cup 2010 Australia round
Le, T. (Recipient), 2010
Prize: Prize (including medals and awards)