STAFF PROFILE
Dr. Su Nguyen
Su Nguyen is a Senior Lecturer in AI and Analytics at RMIT University, Australia.
Su Nguyen's research is at the intersections of artificial intelligence, analytics, and operations research to address concerns towards a sustainable and safe future powered by advanced technologies such as AI, big data, and automation. His research focuses on making AI systems transparent and accountable to improve their acceptance in critical domains such as business, healthcare, and security. He designed and implemented AI innovations to learn and address real-world problems in dynamic, uncertain, complex environments while ensuring autonomous systems can understand fairness and self-correct their behaviours to mitigate discrimination and related risks.
He has been actively collaborating with leading researchers in Australia, New Zealand, Vietnam and the Asia Pacific region to promote the use of AI, analytics, and operations research in industry applications through training, research, and industry engagement.
- PhD in Artificial Intelligence and Operations Research, Victoria University of Wellington, NZ
- Master of Engineering in Industrial Engineering and Management, Asian Institute of Technology, Thailand
- Bachelor of Engineering in Industrial and Systems Engineering, Ho Chi Minh University of Technology (VNU), Vietnam
- Zhang, F.,Mei, Y.,Nguyen, S.,Zhang, M. (2024). Survey on Genetic Programming and Machine Learning Techniques for Heuristic Design in Job Shop Scheduling In: IEEE Transactions on Evolutionary Computation, 28, 147 - 167
- Thiruvady, D.,Nguyen, P.,Sun, Y.,Shiri, F.,Zaidi, N.,Li, X. (2024). Adaptive population-based simulated annealing for resource constrained job scheduling with uncertainty In: International Journal of Production Research, , 1 - 24
- Saeed, N.,Nguyen, S.,Cullinane, K.,Gekara, V.,Chhetri, P. (2023). Forecasting container freight rates using the Prophet forecasting method In: Transport Policy, 133, 86 - 107
- Wu, J.,Nguyen, S.,Alahakoon, D. (2023). Explainable Network Pruning for Model Acceleration Based on Filter Similarity and Importance In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Auckland, New Zealand, 24/11/2022-25/11/2022
- Tran, B.,Sudusinghe, C.,Nguyen, S.,Alahakoon, D. (2023). Building interpretable predictive models with context-aware evolutionary learning In: Applied Soft Computing, 132, 1 - 13
- Zhang, F.,Mei, Y.,Nguyen, S.,Zhang, M. (2023). Multitask Multiobjective Genetic Programming for Automated Scheduling Heuristic Learning in Dynamic Flexible Job-Shop Scheduling In: IEEE Transactions on Cybernetics, 53, 4473 - 4486
- Zhang, F.,Mei, Y.,Nguyen, S.,Tan, K.,Zhang, M. (2023). Task Relatedness Based Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling In: IEEE Transactions on Evolutionary Computation, 27, 1705 - 1719
- Zhang, F.,Mei, Y.,Nguyen, S.,Tan, K.,Zhang, M. (2023). Instance Rotation Based Surrogate in Genetic Programming with Brood Recombination for Dynamic Job Shop Scheduling In: IEEE Transactions on Evolutionary Computation, 27, 1192 - 1206
- Nguyen, S.,O’Keefe, G.,Arisian, S.,Trentelman, K.,Alahakoon, D. (2023). Leveraging explainable AI for enhanced decision making in humanitarian logistics: An Adversarial CoevoluTION (ACTION) framework In: International Journal of Disaster Risk Reduction, 97, 1 - 19
- Zhang, F.,Mei, Y.,Nguyen, S.,Zhang, M. (2022). Importance-Aware Genetic Programming for Automated Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling In: Proceedings of the 17th International Conference, PPSN 2022, Dortmund, Germany, 10/9/2022--14/9/2022
2 PhD Current Supervisions
- Logistics strategies to enhance landforce mobilisation and littoral operations to protect northern Australia from the security threats in the Indo-Pacific [Army Research Scheme 2023]. Funded by: Department of Defence Contract from (2024 to 2025)