Computational and applied mathematics along with data science play a vital role in contemporary society by driving innovation. This success can be attributed to revolutionary theoretical and algorithmic developments in machine learning, data driven modeling, differential equations, numerical analysis, scientific computing, control, optimization, and computing resources together with new tools to deal with uncertainty and randomness.
This journal encourages new research in these broad areas. In addition to research on algorithmic and analytical developments, the journal also encourages papers related to (but not limited to) broad applications in Signal and Image Processing, Computer Vision, Materials Science, Mathematical Biology and Bioengineering. As a result, the journal will be an excellent connecting bridge between mathematical research and real world applications.
The journal accepts high-quality articles containing original research results and survey articles of exceptional merit. Below are short descriptions of the scope of the Areas within the journal:
Computer Science, Mathematics, and Statistics are the infrastructure and baseline of the development of data science, with crucial topics including optimization, operational research, scientific computing, and so on. In data science section of this journal, we are interested in submissions that can advance cutting-edge research in computational, mathematical, and statistical methods and models in data science, and solve important theoretical, numerical, and practical questions remain unsolved or even completely open, in data science.
Numerical Analysis and Scientific Computing:
Numerical methods for ODEs/PDEs, Inverse problems, Optimisation and Control, Model reductions, Uncertainty quantification, computational science and engineering, computational mechanics
Partial Differential Equations and Mathematical Physics:
The Partial Differential Equations and Mathematical Physics section accepts papers on all aspects of ordinary, partial differential equations and mathematical physics. The section also covers all applications concerning partial differential equations.
The Control section welcomes contributions on the Control theory considered in a broad sense, comprising areas of Controllability, Optimal control, Control engineering, Inverse problems, etc. The papers must provide novel theoretical and/or application approaches to non-isolated research topics whose relevance has to be justified with clear links to established methods and theories.
Stochastic Modeling, Analysis and Uncertainty Quantification:
This section accepts research papers on financial markets and population system related stochastic models, analysis of models, including stability and optimal control.
Mathematical Biology and Bioengineering:
We welcome innovative simple mathematical modeling efforts inspired by biological phenomena, including but not limited to ecology and epidemiology. We also welcome the analysis of mathematical properties of existing models with biological implications through new technologies.
The Computer Vision section accepts papers on optimization techniques related to machine learning, computer vision and intelligent control systems. Relevant topics include image processing, target tracking, intelligent systems for the aged care and remote sensing.
The Materials Science section accepts papers on mathematical approaches to describe the behaviour of materials, e.g., in engineering or life science applications. Relevant topics include physics of solids and soft materials, coupled problems, and material modelling.