Artificial Intelligence for Advanced Engineering: Techniques, Methods, and Frameworks

Dear Colleagues,

Artificial intelligence (AI) has gained enormous popularity, both from a theoretical point of view and for its significant and impactful applications. This Special Issue aims to explore the latest techniques, methods, and frameworks in AI specifically tailored for advanced engineering applications. In particular, it will offer a comprehensive insight into AI techniques, such as machine learning, neural networks, and natural language processing, and their applications in various engineering disciplines, including mechanical, electrical, civil, and aerospace engineering. Topics will include, but are not limited to, AI-based design ptimization, predictive maintenance, autonomous systems, and decision-making processes in complex engineering settings. Furthermore, this special issue will also focus on the ethical considerations and challenges associated with integrating AI into engineering workflows, providing insights into ensuring transparency, fairness, and accountability. We invite contributions that demonstrate novel approaches, theoretical insights, practical implementations, and real-world applications of AI in diverse engineering domains, including (but not limited to) the following:

• Predictive maintenance using AI for industrial systems;
• Reinforcement learning for autonomous systems in manufacturing;
• Deep learning approaches for image recognition in civil engineering;
• Optimisation algorithms for energy-efficient building design;
• AI-driven robotics for hazardous environment exploration;
• Natural language processing for automated code generation in software engineering;
• Machine learning techniques for fault detection in electrical power systems;
• AI-based predictive modelling for smart transportation systems;
• Genetic algorithms for optimisation of structural designs in aerospace engineering;
• Intelligent decision support systems for supply chain management in logistics.

Prof. Dr. Marcello Trovati
Dr. Nonso Nnamoko
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• artificial intelligence
• machine learning
• engineering
• reinforcement learning
• deep learning
• robotics
• autonomous systems