The 11th International Conference on Fuzzy Systems and Data Mining (FSDM 2025)

Abstract: This study investigates linear and nonlinear fuzzy Volterra integral equations with piecewise continuous kernels. Existence and uniqueness results are established, and a constructive scheme based on successive approximations is proposed. Numerical experiments are performed for both linear and nonlinear models, supported by error analysis and graphical illustrations. To enhance reliability, the CESTAC method in conjunction with the CADNA library is applied to determine the optimal approximation, optimal fuzzy distance, and optimal step size of the algorithm. Comparative results under different fuzzy parameters confirm the efficiency of the proposed scheme.

Biography: Prof. Samad Noeiaghdam, PhD of Applied Mathematics, is Research Professor of Henan Academy of Sciences, Zhengzhou, China. He was an Associate Professor of Irkutsk National Research Technical University, and a Senior Researcher in South Ural State University, Russia during 2019-2024. His main research interests are numerical analysis, solving mathematical models, fuzzy problems with applications, energy system problems, load leveling in energy storage, supply and demand systems, MHD and heat and mass transfer problems. He has more than 190 publications including several high-quality papers in top journals as well as books, chapters and conference papers. Because of his high-level activities in research and contribution to mathematical advancement globally he has been acknowledged as one of the top 2% scientists by Stanford University. He is the member of editorial board and guest editor in various journals and special issues.

Abstract: In the era of Industry 4.0 and digital transformation, the design of future-ready systems requires more than automation; it demands applied intelligence, a strategic fusion of simulation, mathematical modeling, and data-driven optimization. This keynote explores how intelligent systems, grounded in applied mathematics, are reshaping operations in both industrial and healthcare contexts. Drawing from over two decades of experience, the speaker presents real-world case studies involving simulation-based production planning, metaheuristic-driven resource optimization, and smart monitoring systems implemented in sectors ranging from explosive manufacturing and water processing to packaging and healthcare logistics. The talk highlights how applied intelligence enables predictive decision-making, adaptive workflows, and efficiency improvements under uncertain and dynamic environments. Special attention will be given to the convergence of industrial engineering tools and smart healthcare systems, demonstrating how simulation and AI can be leveraged to optimize hospital operations, manage public health logistics, and enhance service delivery. By unifying theoretical rigor with practical deployment, this talk aims to equip researchers, engineers, and policy-makers with actionable frameworks for building intelligent, scalable, and resilient systems capable of addressing the evolving demands of modern industry and healthcare.

Biography: Asst. Prof. Dr. Nara Samattapapong is a highly respected academic in Industrial Engineering, currently serving at Suranaree University of Technology, Thailand. With a Doctorate in Mechanical Engineering and over 20 years of combined experience in academia and industry, he has built a strong reputation in the areas of intelligent systems, simulation-based optimization, and modern industrial practices. His work emphasizes the application of simulation, data analytics, and AI-enhanced tools to improve efficiency across production, logistics, and quality control processes. Dr. Samattapapong has published over 20 research papers in leading international conferences and journals, including topics such as OEE systems, lean manufacturing, simulation-driven scheduling, and resource optimization using metaheuristics. His recent studies explore intelligent approaches to enhance explosive manufacturing, water processing, and packaging systems. Recognized for his contributions, he has received national awards for excellence in automation and analytical software application. In addition to his research, he has played key roles in academic program development, quality assurance, and curriculum leadership. As a keynote speaker, he brings deep insights into how intelligent systems are transforming industrial operations, bridging theory with practical solutions that address real-world manufacturing challenges in the era of Industry 4.0.

Abstract: To be updated

Biography: Dr. Hongbin Ma has been a Professor at the School of Automation, Beijing Institute of Technology since he joined Beijing Institute of Technology in 2009. He received his bachelor degree from Zhengzhou University in 2001 and doctoral degree from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences in 2006. He joined Bell Labs Research Center at Beijing in March of 2006 and later joined Temasek Laboratories, National University of Singapore in August 2006 as a Research Scientist. His research focuses on adaptation, learning and recognition, especially adaptive estimation and control, as well as their applications in robots, smart cars, and UAVs. He is also a senior member of IEEE and Automation Society of China. Dr. Ma is the principle investigator of several scientific projects supported by National Natural Science Foundation (NSFC), the programme of New Century Excellent Talents in University by Ministry of Education, the programme of Beijing Outstanding Talents Project, and so on. He also won several awards, such as Beijing Natural Science Award, Wu Wenjun Artificial Intelligence Award, Outstanding Research Work Award, etc. Dr. Ma has published more than 100 academic papers in reputable journals or conferences. And under his supervision, a dozen of students have performed well in scientific research, innovation contests, and are establishing themselves.