Computational Statistics《计算统计》（一年8期）. Computational Statistics (CompStat) is an international journal that fosters the publication of applications and methodological research in the field of computational statistics.

Computational Particle Mechanics《计算粒子力学》（双月刊）. Computational Particle Mechanics focuses on the modeling and simulation of systems involving particle mechanics and particle-based methods.

Computational Optimization and Applications《计算优化及其应用》（一年9期）. Computational Optimization and Applications is a peer reviewed journal that is committed to timely publication of research and tutorial papers on the analysis and development of computational algorithms and modeling technology for optimization. Algorithms either for general classes of optimization problems or for more specific applied problems are of interest. Stochastic algorithms as well as deterministic algorithms will be considered. Papers that can provide both theoretical analysis, along with carefully designed computational experiments, are particularly welcome.

Computational Methods in Applied Mathematics《应用数学中的计算方法》（季刊）. The highly selective international mathematical journal Computational Methods in Applied Mathematics (CMAM) considers original mathematical contributions to computational methods and numerical analysis with applications mainly related to PDEs.

Computational Methods and Function Theory《计算方法与函数论》（季刊）. CMFT is an international mathematics journal which publishes carefully selected original research papers in complex analysis (in a broad sense), and on applications or computational methods related to complex analysis. Survey articles of high standard and current interest can be considered for publication as well. Contributed papers should be written in English (exceptions in rare cases are tolerated), and in a lucid, expository style. Papers should not exceed 30 printed pages.

Computational Mechanics《计算力学》（月刊）. The journal reports original research of scholarly value in computational engineering and sciences. It focuses on areas that involve and enrich the application of mechanics, mathematics and numerical methods. It covers new methods and computationally-challenging technologies.

Computational Mathematics and Mathematical Physics《计算数学与数学物理》（月刊）. Computational Mathematics and Mathematical Physics is a monthly journal that publishes reviews and original papers on computational mathematics, computational methods of mathematical physics, informatics, and other mathematical sciences. The journal welcomes reviews and original articles from all countries.

Computational Materials Science《计算材料科学》（一年15期）. The aim of the journal is to publish papers that advance the field of computational materials science through the application of modern computational methods alone or in conjunction with experimental techniques to discover new materials and investigate existing inorganic materials, such as metals, ceramics, composites, semiconductors, nanostructures, 2D materials, metamaterials, and organic materials, such as polymers, liquid crystals, surfactants, emulsions, and also hybrid materials combining both inorganic and organic components such as polymer nanocomposites, nanocrystal superlattices or surfactant nanoparticle mixtures.

Computational Intelligence《计算智能》（双月刊）. This leading international journal promotes and stimulates research in the field of artificial intelligence (AI). Covering a wide range of issues - from the tools and languages of AI to its philosophical implications - Computational Intelligence provides a vigorous forum for the publication of both experimental and theoretical research, as well as surveys and impact studies. The journal is designed to meet the needs of a wide range of AI workers in academic and industrial research.

Computational Geosciences《计算地球科学》（双月刊）. Computational Geosciences publishes high quality papers on mathematical modeling, simulation, numerical analysis, and other computational aspects of the geosciences. In particular the journal is focused on advanced numerical methods for the simulation of subsurface flow and transport, and associated aspects such as discretization, gridding, upscaling, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing.