Autor: Natalia Hartono

Duc Truong Pham Ph.D. DEng holds the Chance Chair of Engineering at the University of Birmingham where he started his career as a lecturer in robotics and control engineering following undergraduate and postgraduate studies at the University of Canterbury in New Zealand. Before returning to Birmingham in 2011, he was Professor of Computer-Controlled Manufacture and Director of the Manufacturing Engineering Centre at Cardiff University. His research is in the areas of intelligent systems, robotics and autonomous systems, and advanced manufacturing technology. He has graduated more than 100 Ph.D. students and, together with them and other research collaborators, has published over 600 technical papers including the original article on the Bees Algorithm. He is a recipient of several awards, notably five best paper prizes from the Institution of Mechanical Engineers, a Lifetime Achievement Award from the World Automation Congress, and a Distinguished International Academic Contribution Award from the IEEE. Natalia Hartono Ph.D. has been a lecturer in Indonesia since 2004 following undergraduate studies in Industrial Engineering at Maranatha Christian University and postgraduate studies in Industrial Engineering and Management at Bandung Institute of Technology, also in Indonesia. In 2019, she received a scholarship from the Indonesian Endowment Fund for Education for her Doctoral Studies at the University of Birmingham where she earned her doctorate in 2023. Her research interests include operations research, supply chain management, product planning and design, the Bees Algorithm, intelligent systems, remanufacturing, circular economy, sustainability modelling, and multi-criteria decision-making. She is part of the Bees Algorithm Research Group and Autonomous Remanufacturing Group at the University of Birmingham. Dr. Hartono is well-known as the co-chair of the International Workshop Series on the Bees Algorithm and Its Applications and the co-editor of the Springer book “Intelligent Production and Manufacturing Optimisation – The Bees Algorithm Approach.”