Associate Professor Saber Elsayed serves at the School of Systems & Computing within the School of Engineering and Information Technology at UNSW Canberra, University of New South Wales, Australia. He was awarded a PhD degree in Computer Science from UNSW Canberra in 2012. His primary research focus areas include computational intelligence and swarm guidance, alongside interests in evolutionary computation, swarm control, planning, and scheduling. Fields of Research associated with his work encompass Optimisation, Neural, Evolutionary and Fuzzy Computation, Decision Making, and Decision Support and Group Support Systems. These contributions have led to advancements in defence, logistics, engineering, and business sectors.

Elsayed holds the position of Associate Editor for the IEEE Transactions on Evolutionary Computation and is a Senior Member of IEEE. From 2019 to 2020, he chaired the IEEE Computational Intelligence Society ACT Chapter and currently serves on its Summer School subcommittee. He has contributed to organizing several international conferences. His accolades include winning the IEEE WCCI/CEC 2022 Competition on Seeking Multiple Optima in Dynamic Environment, the IEEE WCCI/CEC 2022 Competition on Dynamic Optimization Problems Generated by Generalized Moving Peaks Benchmark, the IEEE WCCI/CEC 2020 Competition on Niching Methods for Multimodal Optimization, the GECCO 2020 Competition on Niching Methods for Multimodal Optimization, and IEEE-CEC competitions on Real-Parameter Numerical Optimization in 2020, 2016, 2014, and the 2011 competition on Testing Evolutionary Algorithms on Real-world Numerical Optimization Problems. Additional honors comprise the UNSW Publication Fellowship, High Impact Journal Publications top-up scholarship in 2011, and Postgraduate Research Support Scheme funding in 2011. Notable publications include the edited book Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling (Springer, 2022); book chapters such as 'Large-Scale Swarm Control in Cluttered Environments' (2024), 'Vehicle Routing Problem for an Integrated Electric Vehicles and Drones System' (2023), 'A New Model for the Project Portfolio Selection and Scheduling Problem with Defence Capability Options' (2022), and 'Evolutionary Approaches for Project Portfolio Optimization: An Overview' (2022); as well as supervision of the Best Student Paper award-winning work 'Deep Learning For Noisy Communication System' at ITNAC 2021.

Professional Email: s.elsayed@unsw.edu.au