Personal profile
Biography
Professor Dinh Phung is Head of of the Machine Learning Group and the former Head of the Department of Data Science and AI at Monash University. His research interest includes machine learning, deep learning, generative AI, robust and trustworthy AI, optimal transport, Bayesian and graphical models. He has published 250+ papers in these areas and application domains such as natural language processing (NLP), computer vision, digital health, cybersecurity and autism.
Prospective PhD students, Postdocs and Tutors: Thank you for your interest and for reaching out to me. While I'm keen on receiving strong applications and your EoI, due to the large volume of such emails, please accept my apology in advance if you do not receive a response from me individually as I might only be able to respond to short-listed or selected EoI. Please see this link for further information regarding PhD scholarship and admission at Monash.
Education/Academic qualification
Computer Science, Doctor of Philosophy, Curtin University
Award Date: 17 Jun 2005
Computer Science, Bachelor of Science (Honours), Curtin University
Award Date: 3 Sept 2001
Research area keywords
- Machine Learning
- artificial intelligence
- deep learning
- representation learning
- Bayesian statistics
- graphical models
- generative AI
- optimal transport
- robust and adversarial machine learning
- NLP and computer vision
- digital health
- cybersecurity
- medical AI
- autism
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 -
SDG 13 Climate Action -
SDG 16 Peace, Justice and Strong Institutions
Collaborations and top research areas from the last five years
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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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Project 44 - Generative architectural design engine
Cruz Gambardella, C. (Primary Chief Investigator (PCI)), Phung, D. (Chief Investigator (CI)), McCormack, J. (Chief Investigator (CI)), Cai, J. (Chief Investigator (CI)), Murray, S. (Chief Investigator (CI)), Weiss, K. (Chief Investigator (CI)), Patterson, D. (Chief Investigator (CI)), Huang, S. (Chief Investigator (CI)) & Gribble, A. (Chief Investigator (CI))
1/07/23 → 30/06/26
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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Hierarchical Prompt-Enhanced Image Generation Using Hyperbolic Space
Chen, S., Pan, Z., Cai, J., Fang, P., Harandi, M. & Phung, D., 2026, Neural Information Processing - 31st International Conference, ICONIP 2024 Auckland, New Zealand, December 2–6, 2024 Proceedings, Part XI. Mahmud, M., Doborjeh, M., Wong, K., Leung, A. C. S., Doborjeh, Z. & Tanveer, M. (eds.). Singapore Singapore: Springer, p. 121-136 16 p. (Communications in Computer and Information Science; vol. 2292).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
1 Link opens in a new tab Citation (Scopus) -
Active Continual Learning: On Balancing Knowledge Retention and Learnability
Vu, T.-T., Khadivi, S., Ghorbanali, M., Phung, D. & Haffari, G., 2025, AI 2024, AI 2024: Advances in Artificial Intelligence, 37th Australasian Joint Conference on Artificial Intelligence, AI 2024 Melbourne, VIC, Australia, November 25–29, 2024 Proceedings, Part II. Gong, M., Song, Y., Koh, Y. S., Xiang, W. & Wang, D. (eds.). Singapore Singapore: Springer, p. 137-150 14 p. (Lecture Notes in Computer Science; vol. 15443).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research
1 Link opens in a new tab Citation (Scopus) -
DeepVulMatch: Learning and Matching Latent Vulnerability Representations for Dual-Granularity Vulnerability Detection
Fu, M., Le, T., Nguyen, V., Tantithamthavorn, C. & Phung, D., 2025, In: IEEE Transactions on Reliability. 74, 4, p. 4930-4943 14 p.Research output: Contribution to journal › Article › Research › peer-review
1 Link opens in a new tab Citation (Scopus) -
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
2 Link opens in a new tab Citations (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 Access2 Link opens in a new tab Citations (Scopus)
Activities
- 1 Membership of an advisory panel/policy group/ board
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Victorian Parliamentary Library (External organisation)
Batstone, J. (Member) & Phung, D. (Contributor)
19 Oct 2023Activity: Industry, Government and Philanthropy Engagement and Partnerships › Membership of an advisory panel/policy group/ board