10th International Conference on Applied Mathematics and Sciences (AMA 2026)

10th International Conference on Applied Mathematics
and Sciences (AMA 2026)
May 30 ~ 31, 2026, Virtual Conference
https://ama2026.org/index

Call for Papers;

The 10th International Conference on Applied Mathematics and Sciences (AMA 2026) serves as a premier global forum for the presentation and exchange of innovative ideas, research findings, and emerging trends in the mathematical and scientific disciplines. As the fields of mathematics and applied sciences continue to evolve rapidly, AMA 2026 provides an essential platform for showcasing both theoretical advancements and practical applications that contribute fundamentally to scientific and technological progress.
AMA 2026 welcomes original research papers, state of the art reviews, and innovative studies that advance knowledge across all areas of mathematics and applied sciences. The conference seeks contributions that not only deepen theoretical understanding but also demonstrate impactful real world applications in engineering, technology, industry, and beyond.
Through this collaborative environment, AMA 2026 aspires to inspire new directions in research, support the dissemination of high quality scientific work, and contribute to the continued growth and global relevance of applied mathematics and the sciences.
Topics of interest include, but are not limited to, the following;


Mathematics
 Algebra, Number Theory and Applications
 Differential Geometry and Geometric Analysis
 Topology, Algebraic Topology and Applications
 Real and Complex Analysis
 Functional Analysis and Operator Theory
 Set Theory, Logic and Foundations
 Discrete Mathematics, Combinatorics and Graph Theory
 Network Theory and Complex Networks
Applied Mathematics and Mathematical Modelling
 Mathematical Modelling in Science, Engineering and Industry
 Multiscale, Multiphysics and Complex Systems Modelling
 Stochastic Modelling and Stochastic Processes
 Ordinary and Partial Differential Equations (ODEs and PDEs)
 Dynamical Systems, Chaos Theory and Nonlinear Science
 Fractional Calculus and Fractional Differential Equations
 Inverse Problems and Ill posed Problems
 Mathematical Biology, Epidemiology and Systems Biology
 Bioinformatics, Computational Genomics and Biomedical Modelling
 Mathematical Finance, Risk Modelling and Actuarial Science
 Climate, Environmental and Sustainability Modelling
 Data Assimilation and Extreme Event Modelling
 Computational Social Science and Collective Behaviour
Numerical Analysis, Scientific Computing and High Performance Computing
 Numerical Linear Algebra and Numerical PDEs
 Scientific Computing and Computational Mathematics
 High Performance Computing (HPC), GPU and Exascale Computing
 Parallel, Distributed and Cloud based Algorithms
 AI accelerated Numerical Methods and Neural PDE Solvers
 Surrogate Modelling and Reduced Order Modelling
 Uncertainty Quantification (UQ) and Probabilistic Numerics
 Computational Fluid Dynamics (CFD)
 Computational Physics, Chemistry and Materials Science
 Scientific Machine Learning (SciML)
 Performance Portable Mathematical Software
Optimization, Operations Research and Decision Sciences
 Linear, Nonlinear, Convex and Non convex Optimization
 Global Optimization, Metaheuristics and Evolutionary Computation
 Integer, Combinatorial and Discrete Optimization
 Multi objective Optimization and Decision making
 Operations Research, Logistics and Supply Chain Modelling
 Game Theory, Mechanism Design and Optimal Transport
 Variational Methods and Applications
 Riemannian Optimization and Geometric Optimization
 Federated, Distributed and Stochastic Optimization
 Minimax Optimization and Adversarial Methods
Control Theory, Systems Science and Automation
 Linear and Nonlinear Control Systems
 Optimal, Robust and Adaptive Control
 Stochastic Control, Filtering and Estimation
 Model Predictive Control (MPC) and Real time Optimization
 Networked, Distributed and Cyber Physical Control Systems
 Hybrid Dynamical Systems and Automata Theory
 Sliding Mode Control and Variable Structure Systems
 System Identification and Data Driven Control
 Reinforcement Learning for Control and Safe RL
 Fault Detection, Diagnosis and Fault Tolerant Control
 Control of Autonomous Systems, Robotics and Intelligent Systems
 Multi agent Systems, Swarm Control and Cooperative Decision making
 Verified, Safe and Explainable Control
Artificial Intelligence, Machine Learning and Computational Intelligence
 Mathematical Foundations of Machine Learning
 Optimization Methods for ML and Deep Learning
 Neural Networks, Deep Learning and Approximation Theory
 Generative Models, Diffusion Models and Mathematical Foundations
 Scaling Laws and Theory of Large AI Models (LLMs, Transformers)
 Physics Informed Neural Networks (PINNs) and Operator Learning
 Reinforcement Learning, Control RL and Decision making
 Explainable AI (XAI), Trustworthy AI and Robust ML
 Fuzzy Systems, Neuro Fuzzy Modelling and Uncertainty Handling
 AI for Scientific Discovery and Mathematical Reasoning
Algorithms, Complexity and Theoretical Computer Science
 Algorithms and Data Structures
 Computational Complexity Theory
 Approximation Algorithms and Randomized Algorithms
 Quantum Algorithms, Quantum Information and Quantum Control
 Cryptography, Coding Theory and Information Security
 Post Quantum Cryptography and Lattice based Methods
 Algorithmic Game Theory and Network Algorithms
 Learning Theory (PAC Bayes, Online Learning, Regret Minimization)
 Property Testing and Sublinear Algorithms
 Topological Data Analysis (TDA) and Computational Geometry
Interdisciplinary Applications of Mathematics
 Mathematical Methods in Medicine, Health and Epidemiology
 Mathematical Approaches in Agriculture and Environmental Sciences
 Space, Aerospace and Defense Applications
 Industrial Mathematics and Engineering Applications
 Smart Cities, Energy Systems and Infrastructure Modelling
 Materials Modelling, Nanotechnology and Semiconductor Mathematics
 Mathematical Foundations of Robotics and Autonomous Systems
 Mathematical Physics, Statistical Mechanics and Integrable Systems
 Kinetic Theory and Interacting Particle Systems
Statistics, Probability and Data Science
 Probability Theory and Stochastic Processes
 Mathematical Statistics and Statistical Inference
 Bayesian Methods and Computational Statistics
 Time Series Analysis and Forecasting
 Spatial Statistics and Geostatistics
 Statistical Learning, Data driven Modelling and Big Data Analytics
 High dimensional Statistics and Random Matrix Theory
 Uncertainty Quantification in Data Science

Paper Submission
Authors are invited to submit papers through the conference Submission System by May 23 ,2026 (Final Call). Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Mathematics and Sciences: An International Journal (MathSJ) (Confirmed).

Selected papers from AMA 2026, after further revisions, will be published in the special issue of the following journal.

• International Journal of Advanced Information Technology (IJAIT)
• International Journal of Computer Science, Engineering and Applications (IJCSEA)
• International Journal on Information Theory (IJIT)
• International Journal in Foundations of Computer Science & Technology (IJFCST)


Important Dates;

• Submission Deadline; May 23, 2026 (Final Call)
• Authors Notification; May 28, 2026
• Registration & camera - Ready Paper Due; May 29, 2026

Contact Us;
Here's where you can reach us :[email protected](or) [email protected]
Submission System URL; https://ama2026.org/submission/index.php
For More Information ;https://ama2026.org/index
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