Aim & Scope

Aim

The International Journal of Artificial Intelligence and Machine Learning in Engineering (IJAIMLE) aims to provide a high-quality, peer-reviewed international platform for researchers, academicians, industry professionals, and practitioners to publish innovative research in the rapidly evolving fields of Artificial Intelligence (AI) and Machine Learning (ML) applied to engineering domains. The journal seeks to promote interdisciplinary research that integrates intelligent algorithms, data-driven models, and computational techniques to solve complex real-world engineering problems.

The journal is committed to advancing both theoretical foundations and practical implementations of AI/ML methodologies that enhance automation, optimization, predictive analysis, decision-making, and system intelligence across diverse engineering applications.

Scope

The journal welcomes original research articles, review papers, case studies, and technical communications in, but not limited to, the following areas:

  • Artificial Intelligence techniques in engineering systems

  • Machine Learning and Deep Learning applications

  • Neural Networks and Evolutionary Computing

  • Intelligent Control Systems and Robotics

  • Data Mining and Big Data Analytics

  • Computer Vision and Image Processing in engineering

  • Natural Language Processing for industrial applications

  • AI in Smart Manufacturing and Industry 4.0

  • Predictive Maintenance and Fault Diagnosis

  • IoT-enabled Intelligent Systems

  • Cyber-Physical Systems and Embedded AI

  • AI in Civil, Mechanical, Electrical, and Computer Engineering

  • Optimization Algorithms and Metaheuristic Methods

  • AI-driven Sustainable Energy Systems

  • Cloud-based AI Engineering Solutions