Dr Mohammed Al-Khalidi is an associate professor in Cyber Security and leader of the Cyber Security Research Lab at the Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, UK. He has 20 years of academic and industrial experience in the fields of Cyber Security, Networking, and AI. He is a senior member of IEEE, a member of several technical societies, and a distinguished speaker with more than 50 international keynote speeches. He has been awarded research funding by UKRI's Global Challenges Research Fund (GCRF), The UK Department for Science, Innovation, and Technology (DSIT), and other government bodies focussing on AI Security and Network Security. His past assignments include Lecturer with the Department of Computer Science, Edge Hill University, UK, and Research Officer with the School of Computer Science and Electronic Engineering, University of Essex, UK, where he also received his PhD degree. Prior to that, he worked in industry as a Senior Core Network Engineer at several multinational telecommunication companies. His research interests include AI security, IoT security, Mobile Computing, Cloud Computing, Ad-Hoc Networks, and Information Centric Networks.
Speech Title: Designing Secure and Trustworthy AI for the Next Generation of Intelligent Systems
Abstract: This talk presents an integrated exploration of how trustworthy AI systems can be designed and deployed in real-world contexts. It begins with FarmSense, an IoT-enabled AI platform that transforms soil data into actionable insights for smallholder farmers, demonstrating how intelligent computing can advance food sustainability and resilience. Building on this applied foundation, the talk presents key findings from research on AI security and reliability, offering insights that enhance model robustness against adversarial attacks and inform the development of secure and resilient AI systems. The talk bridges lessons from applied IoT analytics and advances in AI security, contributing to the next generation of resilient intelligent systems.
Dr. Nguyen Minh Tuan
Posts and Telecommunications Institute of Technology, Vietnam
Nguyen Minh Tuan is a computer scientist from Ho Chi Minh City, Vietnam, currently serving at the Posts and Telecommunications Institute of Technology (PTIT). He earned his Ph.D. in Applied Mathematics and Computer Science from King Mongkut's University of Technology North Bangkok, Thailand. He also holds a Master's degree in Mathematics from the University of Science, Ho Chi Minh City, and a Bachelor's degree in Mathematics and Computer Science from Can Tho University, Vietnam. From 2012 to 2020, Dr. Tuan was a lecturer at Ho Chi Minh City University of Technology College. His research interests include intelligent computing, metaheuristic optimization, and advanced machine learning models. He is currently pursuing further academic development at FernUniversität in Hagen, Germany, focusing on hybrid optimization and computational intelligence.
Speech Title: Interdisciplinary Research for the Digital Transformation Era: From Foundations to Applications
Abstract: The rapid advancement of digital technologies has redefined the boundaries of traditional disciplines, creating an urgent need for interdisciplinary research that bridges foundational theories with practical applications. This presentation explores the integration of computational intelligence, data science, and systems engineering as the core pillars driving digital transformation in diverse sectors such as healthcare, education, and smart infrastructure. Emphasis is placed on developing hybrid intelligent systems that combine machine learning with metaheuristic optimization to enhance decision-making accuracy, scalability, and adaptability in complex environments. From a foundational perspective, the talk discusses algorithmic design principles that enable robust data processing, knowledge representation, and predictive analytics. On the application side, several real-world case studies including healthcare data prediction, intelligent diagnostics, and automated resource management are presented to demonstrate the tangible impact of interdisciplinary collaboration. The goal is to perform how cross-domain methodologies not only accelerate technological innovation but also ensure ethical, sustainable, and human-centered digital transformation. Ultimately, this research advocates a holistic approach that unites computational foundations with real-world problem-solving, paving the way toward a smarter, data-driven society.
