The IPS Journal of Mathematics, Computing and Statistics publishes high-quality, peer-reviewed research articles, reviews, and short communications that advance knowledge and applications in the mathematical, computational, and statistical sciences. The journal serves as a platform for theoretical developments, methodological innovations, and practical applications across diverse fields of science, engineering, technology, and society.

Key areas of coverage include, but are not limited to:

• Pure and Applied Mathematics: algebra, analysis, geometry, topology, number theory, differential equations, mathematical modeling, and applied mathematical methods.

• Computing and Information Science: algorithms, artificial intelligence, machine learning, data science, computational mathematics, high-performance computing, software engineering, and emerging technologies.

• Statistics and Data Analysis: statistical theory, biostatistics, econometrics, Bayesian methods, multivariate analysis, time series, probability theory, statistical modeling, and data-driven decision-making.

• Interdisciplinary Applications: quantitative methods in physical sciences, life sciences, engineering, health, finance, environmental science, and social sciences.

The journal welcomes original contributions from academics, researchers, and professionals that highlight new theoretical insights, computational tools, statistical methodologies, and real-world applications that promote innovation and problem-solving.