Machine Learning for Civil Engineering: Recent Advances and Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 May 2026 | Viewed by 139
Special Issue Editors
Interests: image processing; machine learning; software engineering
Interests: application of machine learning to civil engineering; application of IoT to civil engineering; machine learning and the environment
Special Issues, Collections and Topics in MDPI journals
Interests: embedded electronics; machine learning; image processing; security and defense; indirect monitoring
Special Issue Information
Dear Colleagues,
The civil engineering sector is undergoing a transformative shift through the integration of machine learning techniques into design, analysis, monitoring and decision-making processes. This Special Issue aims to explore the latest advances and practical applications of machine learning across all branches of civil engineering, including structural health monitoring, geotechnical modeling, hydraulic forecasting, traffic and transport systems, smart infrastructure and construction optimization.
We invite original research articles, review papers and case studies that highlight innovative uses of supervised, unsupervised and reinforced learning techniques in civil engineering contexts. Contributions should emphasize real-world implementations, data challenges, model deployment, interpretability and performance evaluation in operational environments. Studies that critically assess limitations, scalability issues and domain-specific barriers are particularly encouraged.
This Special Issue seeks to bridge the gap between data-driven methods and civil engineering practice, providing a comprehensive reference for researchers, practitioners and policy-makers interested in the integration of AI into infrastructure and the built environment.
Dr. Virginia Mato-Abad
Dr. Alberto José Alvarellos González
Dr. Daniel Carreres Prieto
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 250 words) can be sent to the Editorial Office for assessment.
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. Applied Sciences 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.
Keywords
- machine learning
- civil engineering
- data-driven modeling
- infrastructure systems
- structural engineering
- environmental engineering
- smart cities
- monitoring and prediction
- engineering applications
- artificial intelligence in engineering
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