Frontiers in Applied Mathematics and Statistics is a multidisciplinary journal that publishes rigorously peer-reviewed research exploring both applied and applicable mathematics and statistics.

Led by Field Chief Editor Prof Charles K Chui (Stanford University, USA) and indexed in Web of Science (ESCI), Scopus, and the DOAJ, the journal welcomes submissions on fundamental areas of study as well as the application of mathematics and statistics to fields including physical and biological sciences, medicine, engineering, finance and economics, computer science, and other technologies. Topics of interest include, but are not limited to:

dynamical systems and mathematical neuroscience
mathematical biology, ecology, and oncology
mathematical finance, econometrics, and actuarial science
mathematics of computation
mathematics of data science
mathematical physics
numerical analysis
optimization and operations research
scientific computing
statistics and probability
systems and control theory.

The journal’s scope includes studies on the theory, methods, development, and application of mathematical tools and techniques, statistical methods and analysis, computational methods, algorithms, and simulations. Studies that support and advance the UN’s Sustainable Development Goals (SDGs) are particularly welcome.

Manuscripts that primarily focus on economics, natural language processing, computational linguistics, pure or discrete mathematics with no proposed applications, or risk analysis in non-mathematical contexts are not suitable for publication in this journal.

By communicating scientific knowledge to researchers and the public alike, Frontiers in Applied Mathematics and Statistics is committed to advancing the application of mathematics and statistical techniques to drive scientific developments in other fields.

Impact

Frontiers in Applied Mathematics and Statistics

Mathematical Physics

Statistical and Computational Physics

Numerical Analysis and Scientific Computation

Participating Journals

Frontiers in Physics

Statistical and Computational Physics