Ali Ahrari is a Lecturer at the University of New South Wales, Australia. His current position is funded by the Australia Research Council through the Discovery Early Career Researcher Award. His research concentrates on evolutionary algorithms and their application to engineering optimization. He is a member of the IEEE CIS Task Force on Multimodal Optimization.

Jonathan Fieldsend, is a Professor of Computational Intelligence at the University of Exeter. He has a degree in Economics from Durham University, a Masters in Computational Intelligence from the University of Plymouth and a PhD in Computer Science from the University of Exeter. He has over 150 peer-reviewed publications in the evolutionary computation and machine learning domains, with particular interests in multiple-objective optimisation, and the interface between optimisation and machine learning. Over the years, he has been a co-organiser of a number of different Workshops at GECCO (VizGEC, SAEOpt and EAPwU), as well as EMO Track Chair in GECCO 2019 and GECCO 2020, and Editor-in-Chief of GECCO 2022. He is an Associate Editor of ACM Transactions on Evolutionary Learning and Optimization and is on the IEEE Computational Intelligence Society (CIS) Task Forces on Data-Driven Evolutionary Optimisation of Expensive Problems, on Multi-modal Optimisation, and on Evolutionary Many-Objective Optimisation.

Mike Preuss is assistant professor at LIACS, the Computer Science department of Leiden University. He works in AI, namely game AI, natural computing, and social media computing. Mike received his PhD in 2013 from the Chair of Algorithm Engineering at TU Dortmund, Germany, and was with ERCIS at the WWU Muenster, Germany, from 2013 to 2018. His research interests focus on the field of evolutionary algorithms for real-valued problems, namely on multi-modal and multi-objective optimization, and on computational intelligence and machine learning methods for computer games. Recently, he is also involved in Social Media Computing, and he is publications chair of the upcoming multi-disciplinary MISDOOM conference 2019. He is associate editor of the IEEE ToG journal and has been member of the organizational team of several conferences in the last years, in various functions, as general co-chair, proceedings chair, competition chair, workshops chair.

Xiaodong Li received his B.Sc. degree from Xidian University, Xi'an, China, and Ph.D. degree in Artificial Intelligence from University of Otago, Dunedin, New Zealand, respectively. He is a Professor with the School of Computing Technologies, RMIT University, Melbourne, Australia. His research interests include machine learning, evolutionary computation, neural networks, deep learning, data analytics, multiobjective optimization, operational research, and swarm intelligence. He served as an Associate Editor of the IEEE Transactions on Evolutionary Computation, Swarm Intelligence (Springer), and International Journal of Swarm Intelligence Research. He is a founding member of IEEE CIS Task Force on Swarm Intelligence, a former vice-chair of IEEE Task Force on Multi-modal Optimization, and a former chair of IEEE CIS Task Force on Large Scale Global Optimization. He is the recipient of 2013 ACM SIGEVO Impact Award and 2017 IEEE CIS IEEE Transactions on Evolutionary Computation Outstanding Paper Award. He is an IEEE Fellow.

Michael G. Epitropakis received his B.S., M.S., and Ph.D. degrees from the Department of Mathematics, University of Patras, Patras, Greece. Currently, he is a Lecturer in Foundations of Data Science at the Data Science Institute and the Department of Management Science, Lancaster University, Lancaster, UK. His current research interests include computational intelligence, evolutionary computation, swarm intelligence, machine learning and search≠ based software engineering. He has published more than 35 journal and conference papers. He is an active researcher on Multi≠modal Optimization and a co≠-organized of the special session and competition series on Niching Methods for Multimodal Optimization. He is a member of the IEEE Computational Intelligence Society and the ACM SIGEVO.