About the Journal

The International Journal of Artificial Intelligence and Machine Learning in Engineering is an international, peer-reviewed journal focused on research at the intersection of artificial intelligence (AI), machine learning (ML), and engineering disciplines. It aims to provide a scholarly platform where researchers, engineers, practitioners, and academicians can share original work that advances both the theoretical foundations and practical applications of AI/ML in engineering contexts. The journal accepts original research papers, high-quality review articles, and technical notes that explore innovative algorithms, system designs, and real-world implementations in engineering problems.

The scope of the journal covers broad areas related to artificial intelligence and machine learning as they apply to engineering, including—but not limited to—intelligent systems, data-driven modelling, optimization techniques, neural network applications, deep learning methods, robotics, automation, signal processing, control systems, and smart infrastructure design. The goal is to foster advancements that can improve performance, adaptability, and decision-making in engineered systems.

As an open access or hybrid publication, IJAIML typically publishes papers either online monthly or biannually, depending on the specific journal outlet or publisher version you refer to. Many of these journals operate a double-blind peer review process, where authors’ identities are not disclosed to reviewers to ensure unbiased evaluation of submissions.

Authors are invited to contribute work that not only proposes new models and algorithms but also demonstrates their applicability to real engineering challenges—for example, predictive maintenance, autonomous systems, materials design, energy systems, manufacturing optimization, and other domains where AI/ML techniques can drive innovation.