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ICoMS 2026: International Conference on Mathematics and Statistics

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Submission Date:
2026-06-05
Notification Date:
2026-06-25
Conference Date:
2026-09-11
Location:
Paris, France
Viewed: 986   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

44.1 / 100
Ranked #3,187 of 5,687 conferences · Top 57%

#22 of 69 in Mathematics & Physical Sciences

Limited evidence: this conference is not listed in CCF / ICORE / QUALIS and has no acceptance-rate data on file, so most of the score falls back to the neutral baseline.
Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%) No data - scored at the neutral baseline of 50 —
Community attention (10%)
13
Public record completeness (15%)
35

Inputs used: Researchers who opened this page in the past 24 months: 5

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 25% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-25

Call For Papers

ICoMS 2026 (International Conference on Mathematics and Statistics) is an academic conference held in Paris, France on 2026-09-11. The paper submission deadline is 2026-06-05. Acceptance notifications are sent on 2026-06-25.

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
Last updated by Dou Sun on

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