The 9th International Conference on Mathematics and Statistics, ICoMS 2026 is a major annual international conference which aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all interdisciplinary areas of Mathematics and Statistics to share their experience, and exchange and cross-fertilize their ideas.

ICoMS 2026 conference theme: "Mathematics & Statistics: The Computational Heart of Artificial Intelligence---from Data to Decisions–Bridging Theory and Algorithms in the Era of Intelligent Systems".

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