Tung Nguyen is a postdoctoral research associate at the Industrial AI Centre, University of South Australia. He received his B.Eng. degree in Biomedical Engineering from Hanoi University of Science and Technology, Vietnam in 2015 and his MSc and PhD in Computer Science from the University of New South Wales in 2018 and 2022. His research interests include deep learning, reinforcement learning, agent architecture, trusted autonomous systems, human-machine teaming, and interpretable and explainable artificial intelligence. He has been working in areas of biomedical engineering, computational intelligence, and robotics, with multiple research laboratories in Vietnam and Australia as well as technology companies in the US. His current... Read more
About me
Tung Nguyen is a postdoctoral research associate at the Industrial AI Centre, University of South Australia. He received his B.Eng. degree in Biomedical Engineering from Hanoi University of Science and Technology, Vietnam in 2015 and his MSc and PhD in Computer Science from the University of New South Wales in 2018 and 2022. His research interests include deep learning, reinforcement learning, agent architecture, trusted autonomous systems, human-machine teaming, and interpretable and explainable artificial intelligence. He has been working in areas of biomedical engineering, computational intelligence, and robotics, with multiple research laboratories in Vietnam and Australia as well as technology companies in the US. His current research encompasses designing knowledge representation structure and reasoning within a multimodal information fusion system.
About me
Doctor of Philosophy University of New South Wales
Master of Science University of New South Wales
Engineer in Electronics and Communication Engineering Hanoi University of Science and Technology
Casual Research Staff (2018-2019) - Trusted Autonomy Lab, University of New South Wales
Casual Lecturer - Master of Cyber Security (Online) (2021-2023) - University of New South Wales
Postdoctoral Research Associate (2022-2023) - University of New South Wales
Research
Research outputs for the last seven years are shown below. Some long-standing staff members may have older outputs included. To see earlier years visit ORCID
Open access indicates that an output is open access.
Year | Output |
---|---|
2020 |
4
|
2019 |
1
|
2019 |
12
|
2018 |
10
|
Year | Output |
---|---|
2020 |
4
|
2019 |
1
|
2018 |
10
|
Nguyen, D.T., Singh, H., Elsayed, S., Hunjet, R., and Abbass, H., 2023, June. Multi-Agent Knowledge Transfer in a Society of Interpretable Neural Network Minds for Dynamic Context Formation in Swarm Shepherding. In 2023 International Joint Conference on Neural Networks (IJCNN). IEEE.
Hussein, A., Ghignone, L., Nguyen, T., Salimi, N., Nguyen, H., Wang, M. and Abbass, H.A., 2022, Characterization of Indicators for Adaptive Human-Swarm Teaming. Frontiers in Robotics and AI, p.16.
Nguyen, T. (2022). Interpretable Knowledge Transfer in Communicative Neural-based Swarm-Guidance Agents (Doctoral dissertation, UNSW Sydney).
Nguyen, D.T., Kasmarik, K.E. and Abbass, H.A., 2022. Fusing Interpretable Knowledge During Communication by Neural Network Learning Agents. arXiv preprint arXiv:2204.00272.
Nguyen, D.T., Kasmarik, K.E. and Abbass, H.A., 2021, Towards Interpretable ANNs: An Exact Transformation to Multi‑Class Multivariate Decision Trees arXiv preprint arXiv:2003.04675.
Nguyen, T., Liu, J., Nguyen, H., Kasmarik, K., Anavatti, S., Garratt, M. and Abbass, H., 2020, July. Perceptron‑Learning for Scalable and Transparent Dynamic Formation in Swarm‑on‑Swarm Shepherding. In 2020 International Joint Conference on Neural Networks (IJCNN)(pp. 1‑8). IEEE.
Nguyen, H.T., Nguyen, T.D., Tran, V.P., Garratt, M., Kasmarik, K., Anavatti, S., Barlow, M. and Abbass, H.A., 2020. Continuous deep hierarchical reinforcement learning for ground-air swarm shepherding. arXiv preprint arXiv:2004.11543.
Nguyen, H.T., Nguyen, T., Nguyen, D.V. and Le, T.H., 2019, October. A Hierarchical Deep Deterministic Policy Gradients for Swarm Navigation.In 2019 11th International Conference on Knowledge and Systems Engineering (KSE) (pp. 1‑7). IEEE.
Nguyen, H.T., Nguyen, T.D., Garratt, M., Kasmarik, K., Anavatti, S., Barlow, M. and Abbass, H.A., 2019, December. A deep hierarchical reinforcement learner for aerial shepherding of ground swarms. In International Conference on Neural Information Processing (pp. 658‑669). Springer, Cham.
Nguyen H., Tran P.V., Nguyen D.T., Garratt M., Kasmarik K., Barlow M., Anavatti S., Abbass, H.A. (2018). Apprenticeship Bootstrapping via Deep Learning with a Safety Net for UAV‑UGV Interaction. AAAI Fall Symposium Series, Interactive Learning in Artificial Intelligence forHuman‑Robot Interaction Symposium (AI‑HRI 18), Arlington, Virginia, USA.
Nguyen, T., Nguyen, H., Debie, E., Kasmarik, K., Garratt, M. and Abbass, H., 2018, July. Swarm Q‑learning with knowledge sharing within environments for formation control. In 2018 International Joint Conference on Neural Networks (IJCNN) (pp. 1‑8). IEEE.
Nguyen, T. (2018). K-line Reinforcement Learning for context-aware bots (Doctoral dissertation, UNSW Sydney).
External engagement & recognition
Organisation | Country |
---|---|
Novia University of Applied Sciences | FINLAND |
University of New South Wales | AUSTRALIA |
Vietnam National University, Ho Chi Minh City | VIET NAM |