The journal welcomes high-quality original research articles, critical reviews, and conceptual papers that offer significant contributions to the following thematic areas:
Artificial Intelligence & Machine Learning Paradigms: Deep learning architectures, reinforcement learning, computer vision, natural language processing (NLP), generative AI models, and explainable AI (XAI).
Data Engineering & Intelligent Ecosystems: Big data analytics, cloud, fog, and edge computing integration, cognitive computing, knowledge graph engineering, and advanced semantic networks.
Digital Transformation Frameworks & Industrial IoT: Smart manufacturing, automation, cyber-physical systems, robotic process automation (RPA), digital twin technology, and corporate technology adoption dynamics.
Autonomous Systems & Smart Infrastructure: Robotics, autonomous vehicles, smart grid management, urban computing, algorithmic optimization in logistics, and smart city architectures.
AI Ethics, Governance & Socio-Technical Impacts: Algorithmic bias, data privacy frameworks, regulatory policies for automated systems, AI compliance, and the future of work within automated societies.
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AIPedia: Journal of Artificial Intelligence and Digital Transformation
Frequency: 4 issues per year
