Prof. Ryo Haraguchi
University of Hyogo, Japan

Speech Title: The Art and Science of Cardiac Modeling and Arrhythmia Simulation

Abstract: This keynote explores the art and science of cardiac modeling, where the "science" of creating computationally intensive models, often requiring High-Performance Computing (HPC), is complemented by the "art" of building a sustainable and accessible research ecosystem. I will provide a comprehensive overview of current trends, highlighting how Open Source Software (OSS) and XML-based standards are breaking down barriers by enabling robust model and data sharing. We will also look toward the future, delving into the emerging paradigm of the Digital Twin in cardiology and the software engineering challenges it presents. This talk is an open invitation for the software engineering community to join this exciting and increasingly accessible field of research.

Biography: Ryo Haraguchi received Ph.D. degrees in informatics from Kyoto University, Kyoto, Japan, in 2003. He is currently a Professor at Graduate School of Information Science, University of Hyogo, Japan. His research interests include medical imaging, medical engineering, cardiac arrhythmia, and computational science. He is a member of the Japanese Society of Medical and Biological Engineering, the Japanese Heart Rhythm Society, IEICE, and IEEE.

Prof. Samir Abou El-Seoud
The British University in Egypt, Egypt

Speech Title: A Survey of Recent Technological Innovations and Their Contribution to Improved Precision and Operational Efficiency in Healthcare Practices

Abstract: Medical imaging visualization has recently gained significant attention, as it has become increasingly recognized as a foundational element in diagnosing and treating a wide range of diseases. This review highlights key domains that benefit substantially from advancements in medical visualization, while also examining emerging technological developments enabled by computer graphics, machine learning (ML), and deep learning (DL).

Biography: Professor Samir Abou El-Seoud received his BSc degree in Physics, Electronics and Mathematics from Cairo University in 1967, his Higher Diploma in Computing from Technical University of Darmstadt (TUD) /Germany in 1975 and his Doctor of Science from the same University (TUD) in 1979.
Field of study: Scientific Computations and Parallel Algorithms.
Research interests: Computer Aided Learning, Parallel Algorithms, Mobile Applications, Augmented Learning, Deep and machine learning techniques, AI, Numerical Scientific Computations and Computational Fluid Mechanics.
Teaching Interest: Computer Graphics, Computer Organization, Computer Architecture, Logic and Digital Design, Analysis and Design of Algorithms, Parallel Algorithms, and Data Structure.
Professor El-Seoud held different academic positions at TUD Germany. Latest Full-Professor in 1987. Outside Germany Professor El-Seoud spent different years as a Full-Professor of Computer Science at SQU – Oman, Qatar University, and PSUT-Jordan and acted as a Head of Computer Science for many years. At industrial institutions, Professor El-Seoud worked as Scientific Advisor and Consultant for the GTZ in Germany and was responsible for establishing a postgraduate program leading to M.Sc. degree in Computations at Colombo University / Sri-Lanka (2001 – 2003). He also worked as Application Consultant at Automatic Data Processing Inc., Division Network Services in Frankfurt/Germany (1979 – 1980). Professor El-Seoud joined The British University in Egypt (BUE) in 2012. Currently, he is Basic Science Coordinator at the Faculty of Informatics and Computer Science (ICS) at BUE.
Professor El-Seoud is the General Chair of different International Conferences. Professor El-Seoud has more than 130 publications in international proceedings and international reputable journals.

Assoc. Prof. Ghada Khoriba
Nile University, Egypt

Speech Title: From Solo to Symphony: How Multi-Agent AI is Orchestrating the Future of Industry

Abstract: Current artificial intelligence systems increasingly rely on multi-agent reinforcement learning (MARL) to address complex industrial optimization problems that surpass the capabilities of single-agent approaches. This talk will cover theoretical foundations and practical implementations of MARL in various industrial sectors. Through systematic analysis of industrial case studies, we explore emergent coordination mechanisms, scalability challenges, and performance metrics in real-world deployments. The talk addresses research gaps, including non-stationarity, partial observability, and reward specification in multi-agent environments, while identifying promising directions for advancing the field's theoretical understanding and industrial applicability.

Biography: Dr. Ghada Khoriba is an Associate Professor at the School of Information Technology and Computer Science at Nile University, Egypt. She holds a Ph.D. in Engineering and Computer Science from the University of Tsukuba, Japan (2010), and earned her Master's and Bachelor's degrees in Computer Science from Helwan University, Egypt.
Dr. Khoriba's recent research focuses on LLM/LVMs, multi-agent reinforcement learning, and computer vision applications. She previously served as Head of the Artificial Intelligence Department at Ahram Canadian University and as a Computer Vision Researcher for Egypt's National Digitization Project, MCIT.
She published more than 40+ papers, including Neural Information Processing Systems (NeurIPS) workshop, and she was recognized among the top 40 high-impact researchers at Helwan University. Dr. Khoriba is a member of IEEE Computational Intelligence Society and ACM.

Keynote Speeches of EESP2024

Prof. Farid Meziane University of Derby, UK		Prof. Tarek M. Sobh University of Bridgeport, USA		Assoc. Prof. Harry Yu University of Derby, UK		Dr. Branislav Vuksanovic Military Technological College, Oman
Speech Title: Exploiting Web Resources to Support Automatic Course Design		Speech Title: The Future Reimagined: Disruptive Technologies and the Dawn of the Autonomous Age		Speech Title: Generative AI (LLM) for Software Engineering: Current Work and Challenges and Future Directions		Speech Title: Challenges and Advances in Facial Expression Recognition: From Manual Analysis to Deep Learning