Speaker: Su Nguyen, RMIT University, Australia
Date: 2 December 2024
Time: 7:00 - 9:00pm (Melbourne Time, UTC+11)
Su Nguyen is a Senior Lecturer (AI and Analytics) at RMIT University, Australia. He received his Ph.D. degree in Artificial Intelligence and Operations Research from Victoria University of Wellington (VUW), Wellington, New Zealand, in 2013. His expertise includes simulation-optimization, evolutionary computation, automated algorithm design, interfaces of artificial intelligence and operations research, and their applications in logistics, energy, and transportation. Nguyen has a strong track record in developing simulation models, simulation-based decision support tools, and simulation-optimisation algorithms for industry applications. He has 100+ publications in top peer-reviewed journals and conferences in computational intelligence and operations research. His current research focuses on hybrid intelligence systems that combine the power of modern artificial intelligence technologies and operations research methodologies. He was the chair (2014-2018) of IEEE task force on Evolutionary Scheduling and Combinatorial Optimisation and is a member of IEEE CIS Data Mining and Big Data technical committee. He delivered tutorials about evolutionary simulation-optimisation and AI-based visualisation at Parallel Problem Solving from Nature Conference (2018), IEEE World Congress on Computational Intelligence (2020), and Genetic and Evolutionary Computation Conference (2022).
The complexity of optimisation models has increased significantly because of new sophisticated business models and the ever-changing digital landscape. Solving optimisation models quickly and accurately is challenging. To tackle these challenges, recent research has explored the applications of machine learning to design or enhance optimisation algorithms. Dr. Su Nguyen will provide an overview of this emerging field and discuss different ways in which machine learning can support optimisation. He will focus on evolutionary machine learning to discover heuristics and decisions within optimisation techniques for solve hard combinatorial optimisation problems.
The Webinar went very successful, with 40+ participants.
The video recording of the Webinar can be found here.
The slides of the Webinar can be found here.
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