Aims and Scopes

The journal’s scope includes, but is not limited to:

• Artificial intelligence and intelligent systems
• Machine learning and deep learning
• Data analytics, data science, and data mining
• Big-data technologies and large-scale analytics
• Natural language processing and generative artificial intelligence
• Computer vision, image processing, and pattern recognition
• Explainable, trustworthy, responsible, and ethical artificial intelligence
• Knowledge representation, reasoning, and expert systems
• Computational intelligence and evolutionary algorithms
• Predictive, prescriptive, and decision analytics
• Optimization methods for artificial intelligence and data science
• Reinforcement learning and autonomous systems
• Cloud, edge, and distributed intelligence
• Internet of Things and intelligent cyber-physical systems
• Data privacy, security, governance, and algorithmic fairness
• Artificial intelligence applications in healthcare, engineering, business, finance, education, environmental science, transportation, and other disciplines

The journal particularly encourages interdisciplinary studies that connect artificial intelligence and data analytics with mathematics, statistics, computer science, engineering, and domain-specific knowledge. Contributions proposing new theoretical frameworks, algorithms, datasets, evaluation methods, or reproducible computational approaches are especially welcome.

All submitted manuscripts are evaluated on the basis of originality, scientific rigor, methodological soundness, clarity of presentation, and relevance to the journal’s scope. Through a rigorous peer-review process and a commitment to publication ethics, Canadian Transactions of Data Analytics and Artificial Intelligence seeks to promote reliable, impactful, and responsible scholarship while supporting the international development of data-driven and intelligent technologies.