Mathematical Applications and Statistical Rigor (MASR): Announcements
type: channel
description: Mathematical Applications and Statistical Rigor (MASR) is an international, peer-reviewed scholarly journal devoted to advancing research at the intersection of deep mathematical theory, rigorous statistical methodology, and impactful real-world applications. MASR is founded on the conviction that mathematics and statistics achieve their highest value when they are not only theoretically sound but also decisively relevant to contemporary scientific, technological, and societal challenges. MASR is more than a publication venue; it is a global research community committed to building a durable bridge between abstraction and application. The journal serves as a meeting point for theorists, applied scientists, and interdisciplinary researchers who seek to translate mathematical and statistical innovation into robust, actionable solutions. Researchers are welcome to submit papers to MASR after preparing them according to the SIRG template (Download from here) and following the SIRG Publisher Ethics and Malpractice Statement (See this page). (MASR) follows the SIRG Publisher peer-review process in handling all submitted papers (see this page for more details). By submitting their paper to MASR , authors confirm their agreement to SIRG Publisher terms, conditions, and publication ethics (please check the author page) and (Copyrights page). Frequency: 6 Volumes Annually Editor-in-Chief: <img src="[binary]"> Prof. Dr. A.M. Elsawah Beijing Normal–Hong Kong Baptist University, CHINA. Email: amelsawah@bnbu.edu.cn Elsawah is an established scholar whose research bridges the two foundational pillars of quantitative science: the design of experiments and the analysis of complex data. His work focuses on developing novel methodologies for optimal experimental design in high-dimensional and complex systems, with applications spanning chemistry, engineering, biomedicine, and industrial processes. He is particularly recognized for integrating advanced statistical design with computati…
language: en