Trung Le

Lecturer, Department of Data Science & AI

Emailtrunglm@monash.edu

Research output per year

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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

Network

Recent external collaboration on country level. Dive into details by clicking on the dots.

1 Finished
2 Active

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
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
Cardiorespiratory function as a non-invasive biomarker for detecting seizures with artificial intelligence: Utilising data from long-term patient recordings from an epilepsy monitoring unit
O'Brien, T., Kwan, P., Sivathamboo, S., Perucca, P., Ge, Z., Le, T., Phung, D., Bonnington, P. & Piccenna, L.
8/04/19 → 8/04/20
Project: Research

60 Conference Paper
3 Article
1 Paper

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 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 proceeding › Conference Paper › Research › peer-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 proceeding › Conference Paper › Research › peer-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 proceeding › Conference Paper › Research › peer-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 journal › Article › Research › peer-review

The first prize of Imagine Cup 2010 Australia round
Le, Trung (Recipient), 2010
Prize: Prize (including medals and awards)