Publisher
Journal Description
The International Journal of Artificial Intelligence and Machine Learning (IJAIML) is an international, peer-reviewed, open-access scholarly journal dedicated to advancing research, innovation, and practical applications in artificial intelligence, machine learning, and intelligent computational systems. Published by SvedbergOpen, the journal provides a global platform for researchers, academics, practitioners, and industry experts to disseminate high-quality original research, reviews, and technical contributions addressing emerging challenges in intelligent technologies. The journal emphasizes scientific rigor, methodological innovation, and research that contributes meaningfully to the development of next-generation AI and machine learning systems.
IJAIML seeks to bridge the gap between theoretical developments and real-world applications by encouraging interdisciplinary research that applies artificial intelligence and machine learning to diverse domains, including healthcare, finance, engineering, robotics, communications, and data science. The journal promotes innovation, transparency, reproducibility, and responsible AI development, encouraging researchers to provide sufficient methodological and experimental details to facilitate verification and further advancement. Through its international scope, IJAIML supports the exchange of knowledge and collaboration among researchers working at the forefront of computational intelligence and intelligent systems.
Focus and Scope
The International Journal of Artificial Intelligence and Machine Learning (IJAIML) welcomes original research articles, review papers, technical contributions, and interdisciplinary studies covering the theoretical foundations, methodologies, applications, and emerging developments in artificial intelligence and machine learning. The journal particularly encourages research introducing novel algorithms, computational models, architectures, analytical methods, and intelligent solutions that demonstrate clear scientific contributions and practical relevance. Studies emphasizing reproducibility, transparent experimentation, reliable evaluation, and responsible deployment of AI technologies are strongly encouraged.
The journal’s scope includes, but is not limited to, Machine Learning, including supervised, unsupervised, semi-supervised, and reinforcement learning; Deep Learning and Neural Networks; Natural Language Processing and Large Language Models; Computer Vision and Image Processing; Robotics and Autonomous Systems; Explainable and Interpretable AI; Ethical and Responsible AI; Data Mining and Big Data Analytics; AI in Healthcare and Medical Informatics; AI in Finance and Business Intelligence; Smart Systems; Edge AI and Internet of Things (IoT); Cyber-Physical Systems; Human-AI Interaction; Cognitive Computing; Intelligent Networks; and other emerging areas of computational intelligence. IJAIML welcomes interdisciplinary research that advances the development of scalable, reliable, transparent, and socially responsible intelligent technologies for real-world applications.