Prof M. S. S. El Namaki，
Dean of the VU School of Management, Switzerland

Prof El Namaki is a graduate of the universities of Brussels (Ph. D, 1977), Erasmus (MA, 1967) and MIT (Executive Program, 1982). Prof El Namaki teaches and consults on strategic thinking, entrepreneurship and international business. He is past founder and Dean of the Maastricht School of Management (MSM), Maastricht, The Netherlands (1984-2002). He is now Dean of the VU School of Management, Switzerland. Prof El Namaki has developed and introduced management degree programs (MBA, EMBA, DBA and Ph. D) at institutions in the Netherlands, China, Egypt, Brazil, Poland, Kazakhstan, Syria, Singapore, Malaysia and Indonesia, among others.
Prof El Namaki taught and consulted globally at as recognized institutions as MSM (Maastricht), Helsinki School of Economics (Helsinki), Sheffield University (Sheffield) Kellogg (Chicago), Jiao Tong University (Shanghai), Beijing University (Beijing), AIT (Bangkok), His latest book publications include “Strategic thinking in the age of artificial intelligence “ (2022) and Macmillan’s “ Neo Strategic Management, Conceptual and Operational Foundations of tomorrow’s strategic thinking” (Sept 2023).

Prof. Fairouz Dib Kamareddine
Heriot-Watt University in Scotland, UK

Professor of Theoretical Computer Science in Heriot-Watt University in Scotland, UK. Fairouz Kamareddine has been involved in a number of worldwide consultancy assignments, especially on education and research issues working for United Nations and the EU. Her research interest includes Interface of Mathematics, Logic and Computer Science. She has held a number of invited positions at universities in Europe, Asia and the Americas. She has well over 200 published articles and a number of books. She dedicated to continue to play leading roles in the development, administration, and implementation of interdisciplinary, international, and academic collaborations and networks.

Prof. Thomas Hanne
University of Applied Sciences and Arts Northwestern Switzerland,Switzerland

Thomas Hanne received master's degrees in Economics and Computer Science, and a PhD in Economics. From 1999 to 2007 he worked at the Fraunhofer Institute for Industrial Mathematics (ITWM) as senior scientist. Since then he is Professor for Information Systems at the University of Applied Sciences and Arts Northwestern Switzerland and Head of the Competence Center Systems Engineering since 2012. He is also Honorary Research Chair Professor at Bennett University, Greater Noida, India since 2023.
Thomas Hanne is author of more than 250 journal articles, conference papers, and other publications and editor of several journals and special issues. His current research interests include computational intelligence, evolutionary algorithms, metaheuristics, optimization, simulation, multicriteria decision analysis, machine learning, natural language processing, large language models, systems engineering, software development, logistics, and supply chain management.

Assoc.Prof. Xing Su
Beijing University of Technology, China

Xing Su is an associate professor in the College of ComputerScience, Beijing University of Technology, China. He received his B.Sc in the Schoolof Software Engineering from Beijing University of Technology in 2007. Hereceived his M.Sc and Ph.D in computer science from University of Wollongong,Australia in 2012 and 2015. His research interests include multi-agent system, reinforcementlearning, intelligent transportation system and service-oriented computing.

Assoc. Prof. Chang Liu
University of Chinese Academy of Sciences, China

Assoc. Prof. Liu Chang has long been engaged in theoretical and applied research on complex manufacturing process modeling, production scheduling, and intelligent optimization. She has undertaken multiple national level science and technology projects, including the 863 Program, National Major Science and Technology Projects, and Natural Science Foundation. Her group have accumulated rich theoretical and applied research experience in complex manufacturing system production scheduling and intelligent optimization, as well as closed-loop optimization of production scheduling based on data and knowledge dual drive, forming a comprehensive and in-depth method system. Assoc. Prof. Liu has published over 50 academic papers, over 20 patents and software copyrights, and won the first prize of provincial and ministerial level scientific and technological progress, invention patent award, and 5 scientific research achievements. The "Zhongke Yunyi Intelligent Scheduling System" developed under her leadership, which has been practically applied in discrete and semi process industries.

Assoc. Prof. Ian Tan
Heriot-Watt University's Malaysia, UK

Dr. Ian Tan is an Associate Professor in Computer Science and currently serves as the Head of School, Mathematical and Computer Sciences at Heriot-Watt University's Malaysia campus. With over a decade of industry experience spanning microprocessor manufacturing, enterprise servers, and telecommunications, he brings a unique perspective to academia. Since 2006, Dr. Tan has made significant contributions in teaching, research, and administrative roles, including as Head of Commercialisation and as Industry Engagement Coordinator.
His research focuses on parallel and distributed systems, particularly in operating systems scheduling and blockchain technology, specifically for the latter, in network communication across distributed networks. He is also actively involved in multimedia data analytics, specifically automated essay scoring. Dr. Tan holds a Ph.D. in Information Technology from Multimedia University, an M.Sc. in Parallel Computers and Computation from the University of Warwick, and a B.Eng. in Information Systems Engineering from Imperial College London.

Assoc. Prof. Xin Lu，
Leeds Trinity University, UK

Dr. Xin Lu is an Associate Professor in Computer Science, currently leading research activities at the School of Computer Science at Leeds Trinity University (LTU). With over a decade of dedicated research, Dr. Lu specializes in the design of Big Data analytics and deep learning-empowered Internet of Things (IoT) frameworks for applications spanning Smart Factory and Smart Home domains. His current research endeavors focus on advancing Big Data analysis and deep learning methodologies tailored for Smart Systems, with particular emphasis on Intelligent Manufacturing, Digital Healthcare, and Smart City domains. Noteworthy areas of investigation include Intelligent Edge/Fog-enabled IoT systems and human-robot collaboration methodologies pertinent to Intelligent Manufacturing and Digital Health contexts. Dr. Lu's research interests encompass a spectrum of topics, including Digital Twins, Deep Learning, Generative Artificial Intelligence (AI) in Higher Education, Human-Robot Collaborations, Big Data Analytics, Intelligent Manufacturing, Internet of Things, and TinyML.