Mathematical modelling and computer simulations (MathMo)
Mathematical modelling is a longstanding discipline within applied mathematics, serving as a vital tool for simulation of physical phenomena, technological processes, and various objects across fields such as engineering, physics, biology, and economics. With recent advancements in data sciences, the scope of mathematical methods has expanded significantly, allowing for applying these techniques to problems that require the analysis of multiple sets of microscopic observations in material sciences, biology, etc. Recent new mathematical achievements in the theory of discrete multiple convolutions and boundary value problems can extend the comprehensive tools invaluable for optimizing technological processes, developing novel materials, and making predictive simulations of material properties.
Traditional approaches to partial differential equations (PDE) and numerical schemes have reached their limits in terms of computational costs. In response, emerging fields like image analysis, data processing, and deep machine learning have demonstrated tremendous potential, consistently delivering results that exceed the expectations of engineers and physicists.
11 tracks are dedicated to innovative computational technologies encompassing a broad spectrum of modelling methods. These include areas of interest such as composites, porous media, metamaterials, 2D-3D visualization, and more. Furthermore, 11 tracks emphasize innovative educational technologies related to the utilization of AI and GPT, recognizing their increasing importance in modern education.
By exploring these novel computational technologies, modern constructive mathematical investigations and embracing cutting-edge educational tools, the conference aims to empower researchers, engineers, and practitioners to address complex challenges and create impactful solutions across various domains.