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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

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Projects

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.

15/04/1930/06/21

Project: Research

Deep Learning for Cyber (Data61 CRP 38)

Phung, D., Le, T., Xiang, Y., Zhang, J., Wen, S., Murray, T. & Nock, R.

15/06/1830/06/21

Project: Research

Research Output

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 proceedingConference PaperResearchpeer-review

Open Access
File

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 proceedingConference PaperResearchpeer-review

Open Access
File

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 proceedingConference PaperResearchpeer-review

Open Access

Deep domain adaptation for vulnerable code function identification

Nguyen, V., Le, T., Le, T., Nguyen, K., Devel, O., Montague, P., Qu, L. & Phung, DI., 2019, International Joint Conference on Neural Networks (IJCNN) 2019. Angelov, P. & Roveri, M. (eds.). IEEE, Institute of Electrical and Electronics Engineers, 8 p. 8851923

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

2 Citations (Scopus)

GoGP: scalable geometric-based Gaussian process for online regression

Le, T., Nguyen, K., Nguyen, V., Nguyen, T. D. & Phung, D., 20 Jul 2019, In : Knowledge and Information Systems. p. 197-226 30 p.

Research output: Contribution to journalArticleResearchpeer-review

Prizes

The first prize of Imagine Cup 2010 Australia round

Le, Trung (Recipient), 2010

Prize: Prize (including medals and awards)