2026 9th International Conference on Mathematics and Statistics
We welcome your participation and contribution to the 2026 9th International Conference on Mathematics and Statistics (ICoMS 2026) to be held in Paris, France during September 11-13, 2026.
ICoMS 2026 is organized to bring together worldwide leading researchers and practitioners interested in advancing the state of the art in Mathematics and Statistics, for exchanging knowledge that encompasses a broad range of disciplines among various distinct communities. It is hoped that researchers and practitioners will bring new prospects for collaboration across disciplines and gain inspiration to facilitate novel breakthroughs. The themes for this conference are thus focused on "Cross-disciplinary Innovation and Applications of Mathematics, Statistics, and Computer Science".
Paper Publication
All accepted papers fulfilling requirements on quality will be published in ICoMS 2026 Conference Proceedings. It is mandatory that at least one author registers and presents for every paper that is included in the conference proceedings. The Conference Proceedings will be indexed by EI Compendex and Scopus.
Some excellent papers will be recommended for publication in the Mathematical and Computational Applications (ISSN: 2297-8747) as a special issue, which will be submitted to be indexed by Scopus, ESCI (Web of Science), Inspec, etc. Impact Factor: 2.1, CiteScore: 0.5
For those who are not willing to publish papers, they may submit abstracts. The accepted abstracts can be presented at the conference as Presentation Only.
Please follow the link for electronic submission (Click). Should you have any inquiries, please contact us via icoms@cbees.net.
Review Process
The submitted papers will undergo double-blind review process by at least 2 technical committee members or reviewers. It will be reviewed based on the quality, originality, significance, and relevance to the conference theme. The submissions must not be under consideration for publication elsewhere.
JOIN IN ICoMS 2026 AS A DELEGATE!
For those who do not willing to publish and present papers, you're simply required to fill out the information online for delegates and release the payment before the registration deadline. We'll contact you after we reviewed the registration.
Original papers are solicited in topics including, but not limited to the following:
Data Science and Machine Learning
●Mathematical Foundations of Machine Learning Algorithms
●Deep Learning Techniques in Statistics and Data Science
●Statistical Learning and Pattern Recognition
● Data Mining and Big Data Analytics in Statistics
● Predictive Analytics: Statistical Approaches and Applications
Computational Mathematics and Numerical Analysis
●High-Performance Computing for Mathematical Simulations
●Numerical Methods for Solving Partial Differential Equations
●Scientific Computing in Mathematical and Statistical Applications
●Computational Algebraic Geometry and Applications
●Monte Carlo and Markov Chain Methods in Numerical Analysis
Applied Mathematics and Interdisciplinary Applications
●Mathematical Biology: Modeling in Population Dynamics and Epidemiology
●Mathematical Finance and Risk Management Models
●Computational Fluid Dynamics and Mathematical Models in Physics
●Cryptography, Information Security, and Mathematical Foundations
●Mathematical Methods in Environmental and Climate Studies
Probability Theory and Stochastic Processes
●Advances in Probability Theory and Stochastic Models
●Applications of Stochastic Processes in Finance and Insurance
●Random Walks and Their Applications in Physics and Biology
●Markov Chains and Their Use in Statistical Modeling
●Queueing Theory and its Applications in Network Systems
Time Series Analysis and Forecasting
●Time Series Models for Economic and Financial Forecasting
●Statistical Methods for Forecasting with Big Data
●Econometrics and Statistical Modelling of Time Series Data
●Advanced Techniques in Seasonal Adjustment and Trend Analysis
●Statistical Analysis of Multivariate and Non-Stationary Time Series
Mathematical Modeling and Optimization
●Advanced Mathematical Modeling in Engineering and Sciences
●Optimization Algorithms and Applications in Real-World Problems
●Nonlinear Dynamics and Chaos Theory in Complex Systems
●Multi-Objective Optimization and Decision-Making Techniques
●Computational Methods in Mathematical Programming
Statistical Analysis and Inference
●Modern Techniques in Statistical Inference and Estimation
●Bayesian Methods and Applications in Statistics
●Multivariate Analysis and High-Dimensional Data
●Robust Statistical Methods for Outliers and Incomplete Data
●Hypothesis Testing and Statistical Decision Theory