The journal publishes high-quality original research, review articles, and interdisciplinary studies that advance the mathematical foundations, theoretical developments, and practical applications of Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, and Emerging Computing Technologies. It aims to provide an international platform for researchers, academicians, industry experts, and practitioners to disseminate innovative research addressing current and future challenges in intelligent systems and computational sciences.

The journal welcomes submissions in, but is not limited to, the following areas:

• Numerical and Linear Algebra:

  • Tensor decompositions

  • High-dimensional data analysis

  • Numerical stability in deep learning

• Optimization Theory

  • Non-convex optimization

  • Stochastic Gradient Descent (SGD) variants

  • Evolutionary algorithms for neural architecture search

• Dynamical Systems and Calculus

  • Differential equations for Neural Ordinary Differential Equations (Neural ODEs)

  • Network fluid dynamics

  • System stability analysis

• Probabilistic and Statistical Modeling

  • Bayesian inference and Markov Foundations

  • Computational Uncertainty Quantification (UQ)

  • Time-series predictive modeling

• Neural Network Architectures

  • Transformer models

  • Graph Neural Networks (GNNs)

  • Message-passing algorithms for large-scale networks

• Neuro-Symbolic Artificial Intelligence

  • Integration of deep learning with symbolic reasoning

  • Knowledge representation

  • Formal verification and trustworthy AI

• Explainable Artificial Intelligence (XAI)

  • Mathematical Frameworks (SHAP, LIME)

  • Taylor expansion-based interpretability

  • Transparent and explainable machine learning

• Autonomous and Intelligent Systems

  • Reinforcement learning

  • Self-learning models for Robotic autonomy

  • Autonomous decision-making

• Green Artificial Intelligence Mathematics

  • Energy-efficient optimized AI algorithms

  • Green AI & Computational optimization

  • Sustainable Large Language Models (LLMs)

• Adversarial Machine Learning

  • Adversarial robustness

  • Poisoning and evasion attacks

  • GAN-based defense mechanisms

• Intelligent Cybersecurity

  • AI-Driven Adaptive intrusion Detection Systems

  • Zero-Day Exploit Identification & Predictive Threat Intelligence

  • Scalable Intrusion Prevention over High Speed Networks

• Privacy-Preserving Machine Learning

  • Federated learning

  • Differential privacy

  • Secure learning on encrypted data

• Advanced Cryptography

  • Homomorphic encryption

  • Secure Multi-Party Computation (SMPC)

  • Zero-Knowledge Proofs (ZKPs)

• Game Theory and Cyber Defense

  • Stackelberg games

  • Strategic attacker-defender modeling

  • Security optimization

• Biometrics and Digital Identity

  • AI-based biometric authentication

  • Identity verification & Validation

  • Zero Trust security frameworks

• Graph Theory and Topological Data Analysis

  • Spectral graph theory for Community detection

  • Topological Data Analysis (TDA)

  • Malware detection and analysis

• Blockchain and Web3 Security

  • AI-enhanced Smart contract auditing

  • Formal verification of Decentralized system security

  • Consensus algorithms

• Edge Computing and Distributed Intelligence

  • Lightweight AI models

  • Intelligent Resource-constrained computing

  • AI-enhanced Software-Defined Networking (SDN)

• Security Digital Twins

  • Mathematical modeling

  • Infrastructure security simulation

  • Financial fraud detection

• Quantum Artificial Intelligence

  • Quantum machine learning

  • Quantum optimization

  • Hybrid quantum-classical computing

• Post-Quantum Cryptography

  • Mathematical Models for Lattice-based cryptography

  • Mathematical Models for Code-based cryptography

  • Mathematical Models for Multivariate cryptographic algorithms

• Quantum Security Protocols

  • Quantum Key Distribution (QKD)

  • Quantum-resistant digital signatures

  • Secure quantum communication

The journal encourages interdisciplinary research that bridges mathematics, artificial intelligence, cybersecurity, data science, and emerging computational technologies, promoting innovative theoretical contributions as well as practical applications with significant scientific and societal impact.