Projects per year
Personal profile
Biography
Dinh Phung is a Professor of Machine Learning and DS in the Faculty of Information Technology, Monash University, Australia. He is also currently the Research Director in the newly established Department of Data Science and AI in the Faculty.
His primary interest includes theoretical and applied machine learning with a current focus on deep learning, robust and adversarial ML, optimal transport and point process theory for ML, generative AI, Bayesian nonparametrics and graphical models. He publishes regularly, with over 250+ publications, in the areas of machine learning, AI, data science and application domains such as natural language processing (NLP), computer vision, digital health, cybersecurity and autism. From 2017 - 2020, he split his time at Monash to work as an AI Chief Chief Scientist and Tehcnical Consultant for Trusting Social - an AI Fintech company to provide Digital Identity and eKYC solutions. He is also known in Vietnamese as Phùng Quốc Định and his personal website is located here.
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 Sep 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
Network
Recent external collaboration on country level. Dive into details by clicking on the dots or
Projects
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Towards a National Data Management Platform and Learning Health System
Teede, H., Kannan, A., Andrew, N., Pearce, C., Johnson, A., Enticott, J., Bonnington, P., Dobson, R., Curcin, V., McKimm, A., Wale, R., Bingham, G., Tong, E., Mason, C. W., MacBean, L., Pearce, C., Ferrigi, J., Andrew, N., Beare, R., Srikanth, V., Phung, D., Du, L., Collyer, T., Shaw, T., Snelling, T. L., Keech, W., Geelhood, G. & Wilson, A.
1/02/21 → 30/06/22
Project: Research
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Towards Robust Learning Systems via Amortized Optimization and Domain Adaptation
Le, T., Phung, D., Xiang, Y., Zhang, J., Erfani, S., Rubinstein, B., Leckie, C., Nock, R. & Knight, K.
15/04/19 → 30/06/21
Project: Research
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Using social media data to identify markers of depression risk among individuals: A longitudinal cohort study
O'Dea, B., Larsen, M. E., Venkatesh, S., Phung, D. & Glozier, N.
1/01/19 → 31/12/21
Project: Research
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Deep Learning for Cyber (Data61 CRP 38)
Phung, D., Le, T., Xiang, Y., Zhang, J., Wen, S., Murray, T. & Nock, R.
15/06/18 → 30/06/21
Project: Research
Research output
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A capsule network-based model for learning node embeddings
Nguyen, D. Q., Nguyen, T. D., Nguyen, D. Q. & Phung, D., 2020, Proceedings of the 29th ACM International Conference on Information & Knowledge Management. Hauff, C., Curry, E. & Cudre Mauroux, P. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 3313-3316 4 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
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Code Action Network for binary function scope identification
Nguyen, V., Le, T., Le, T., Nguyen, K., de Vel, O., Montague, P., Grundy, J. & Phung, D., 2020, Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia Conference, PAKDD 2020 Singapore, May 11–14, 2020 Proceedings, Part I. Lauw, H. W., Wong, R. C-W., Ntoulas, A., Lim, E-P., Ng, S-K. & Pan, S. J. (eds.). Cham Switzerland: Springer, p. 712-725 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12084 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile -
Code Pointer Network for binary function scope identification
Nguyen, V., Le, T., Nguyen, K., de Vel, O., Montague, P. & Phung, DI., 2020, 2020 International Joint Conference on Neural Networks (IJCNN), 2020 Conference Proceedings2020 International Joint Conference on Neural Networks, IJCNN 2020 - Proceedings. Roy, A. (ed.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 7 p. 9207293Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
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Deep Cost-Sensitive Kernel Machine for binary software vulnerability detection
Nguyen, T., Le, T., Nguyen, K., de Vel, O., Montague, P., Grundy, J. & Phung, D., 2020, Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia Conference, PAKDD 2020 Singapore, May 11–14, 2020 Proceedings, Part II. Lauw, H. W., Wong, R. C-W., Lim, E-P., Ntoulas, A., Ng, S-K. & Pan, S. J. (eds.). Cham Switzerland: Springer, p. 164-177 14 p. (Lecture Notes in Computer Science; vol. 12085 ).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile -
Dual-component deep domain adaptation: a new approach for cross project software vulnerability detection
Nguyen, V., Le, T., de Vel, O., Montague, P., Grundy, J. & Phung, D., 2020, Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia Conference, PAKDD 2020 Singapore, May 11–14, 2020 Proceedings, Part I. Lauw, H. W., Wong, R. C-W., Ntoulas, A., Lim, E-P., Ng, S-K. & Pan, S. J. (eds.). Cham Switzerland: Springer, p. 699-711 13 p. (Lecture Notes in Computer Science ; vol. 12084 ).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access