https://sciforum.net/event/IOCMA2026
Algebra, Geometry, Topology, and Logic with Applications: This session delves into the core areas of algebra, number theory, differential geometry, complex geometry, mathematical logic, cryptography, and topology, as well as their connections with other scientific and technological domains.
Mathematical Analysis: This session encompasses research in real and complex analysis, differential equations (both ordinary and partial), evolution equations, dynamical systems, functional analysis, calculus of variations, and harmonic analysis with wavelet with applications in biology, finance, fluid mechanics, etc.
Statistics and Operational Research: This session covers recent advances in the theory of probability and statistics, data analysis, operations research, and their applications in many disciplines. It is dedicated to the latest advancements in theoretical research and their various applications.
Applied Mathematics: This session focuses on developing and applying computational techniques to solve complex scientific problems across multiple disciplines. This includes numerical linear algebra, numerical, numerical approximation, computational geometry, and numerical solutions of differential equations, integral equations, and inverse problems.
Control Theory and Mechanics: Submissions reporting novel mathematical methods and computational techniques for control and mechanics issues are welcome for this session. Topics include, but are not limited to, robust control theory, predictive control, nonlinear control, adaptive control, optimal control theory in mechanical systems, stability analysis, mathematics of multibody dynamics, control-oriented parameter identification, multiscale mechanical systems, mechanical contact problems, topology optimization, etc.
Mathematics, Computer Science and Artificial Intelligence: This session aims to showcase the latest research results in the evolving intersection of mathematics, computer science, and artificial intelligence (AI). It places a particular emphasis on the mathematical foundations of AI, such as neural network theory, optimization algorithms for AI, and probability theory in machine learning. Additionally, papers that describe the real-world applications of AI while highlighting the underlying mathematical principles are highly encouraged.