Computational Mathematics & Data Science

BRJMS publishes double-blind, peer-reviewed, high-quality research in Mathematics and Statistics, featuring advanced studies in pure and applied mathematics, statistical theory, data science, and interdisciplinary mathematical applications. Every article is published open access under a CC BY 4.0 license. You keep your copyright, and your work is free to read worldwide from the day it publishes, across multiple channels.

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About Computational Mathematics & Data Science

Computational Mathematics & Data Science is one of the subject areas published in the Boston Research Journal of Mathematics & Statistics. It spans the mathematical and algorithmic foundations of computation, covering numerical linear algebra, finite element and finite difference methods, scientific computing, Monte Carlo methods, uncertainty quantification, and symbolic computation. The area also extends to machine learning theory, statistical learning, data mining, network analytics, and signal and image processing mathematics.

Contributions are sought from authors whose work bridges rigorous mathematical analysis with practical computational methods. The readership draws from computer science, statistics, electrical engineering, and operations research, as well as applied mathematicians who require algorithmic tools to handle large or complex data.

Objective

The objective of our journal is to produce peer-reviewed, authenticated research papers on various theoretical as well as applied disciplines of Computational Mathematics & Data Science prepared by scholars and researchers all across the world. Our journal does not just concern the field of Computational Mathematics & Data Science but also includes all the scopes that are mildly or completely related to these fields providing our authors a single platform for all their works.

Aim & About Journal

The Boston Research Journal of Mathematics & Statistics primarily focuses on statistics and mathematical research. The journal contains original and progressive research papers in these disciplines in order to provide knowledge. We aim to become a reference research publication. We publish and review original and authentic research papers as well as auxiliary materials such as case studies, technical reports, etc. by scholars and researchers all across the world. We welcome the submission of papers concerning any branch of science and mathematics and their application in education, industry, research, and other organizations.

Primary Subjects Under This Discipline

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Pure Mathematics

Exploration of fundamental mathematical concepts and structures, including algebra, analysis, geometry, topology, and number theory, for intrinsic understanding.

Probability Theory & Stochastic Processes

The study of randomness and uncertainty, encompassing the mathematical models for random events, variables, and dynamic systems evolving over time.

Discrete Mathematics & Combinatorics

Study of finite or countable mathematical structures such as graphs, networks, codes, and arrangements, with applications in computer science and operations research.

Applied Mathematics

Development and utilization of mathematical methods and models to solve problems in science, engineering, finance, industry, and other practical domains.

Statistical Theory & Methodology

Foundations and techniques for data collection, analysis, interpretation, and inference, including experimental design, hypothesis testing, and model estimation.

Computational Mathematics & Data Science

Application of computational techniques to mathematical problems and the extraction of knowledge from data, including numerical analysis, optimization, and statistical learning.

Mathematics & Statistics

General mathematical and statistical research spanning algebra, analysis, numerical methods and mathematical finance, including work that crosses the boundaries of the other subject areas.