Manuscript Topics

The aim of this Special Issue is to bring together recent advances in numerical analysis, mathematical modeling, and interdisciplinary scientific computing. Modern mathematical and computational tools play a fundamental role in the analysis and simulation of complex systems arising in a wide range of disciplines, including physics, engineering, biology, big data, game theory, and data-driven decision sciences. In addition, the rapid development of machine learning and artificial intelligence has opened new opportunities for integrating data-driven approaches with traditional numerical and analytical methods.

This Special Issue welcomes high-quality contributions that address both theoretical developments and practical implementations of numerical methods, with particular emphasis on advanced algorithms and analysis, multiscale modeling, optimization, uncertainty quantification, and emerging applications in machine learning and artificial intelligence. We especially encourage submissions that highlight the interplay between mathematical rigor and real-world modeling, and that bridge traditional disciplinary boundaries through innovative analytical or computational techniques. By creating a unified forum for researchers from mathematics, physics, engineering, finance, and economics, this Special Issue aims to foster cross-disciplinary dialogue and advance the state of the art in computational science and applied mathematics.

Keywords: Numerical analysis; Scientific computing; Mathematical modeling; Multiscale methods; Optimization and control; Uncertainty quantification; Machine learning and AI in computation; Data-driven modeling; Interdisciplinary applications

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Please submit your manuscript to online submission system
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