Data-Centric Engineering (Cambridge University Press) is delighted to renew its publishing partnership with ARTISTE2025, a conference dedicated to Artificial Intelligence applications to the Structural Engineering. ARTISE2025 took place 13-17 September 2025. Selected authors are encouraged to develop the abstract presented at the Conference to submit a full paper to DCE as part of an ongoing special collection dedicated to the conference's theme of Artificial Intelligence in Structural Engineering. 

Jump to: 

• About ARTISTE
• Timetable
• How to Submit
• Peer Review
• Why Submit to DCE?
• Open Access
• Guest Editors

About ARTISTE 

Artificial Intelligence (AI) is a wide-ranging branch of computer science concerned with building smart tools capable of performing tasks that typically require human intelligence. Nowadays, as human beings, we use AI in our daily lives, even though we may not always be aware of it. For instance when asking Siri or Alexa to look something up for us, chatting with chatbots like ChatGPT and other alternatives to address our inquiries, or searching things on Google, and even something as simple as the pesky advertisements we get bombarded by online are all related somehow to AI. Although the increase in knowledge has shown in numerous branches in recent decades, Structural Engineering was born much more before the development of many modern sciences. Nevertheless, modern structural engineering as a discipline was systematically formalized over two centuries ago and used the first mathematical and physics applications to analyze and predict structures’ behavior under given loading conditions, providing a tool for designing them in a rational and cost-effective way. The development of specific analysis and computational methods for a wide range of structural problems permitted over the last two hundred years to revolutionize the world of the construction industry, tackling important challenges likewise designing tall buildings, long-span bridges, towers, and generally speaking, our cities and infrastructural systems. What the community currently perceives as a “mature” technology is the result of the advancements and in-depth development of designing procedures and, on the other side, the adoption of industrialized structural materials that permit ensuring mechanical parameters and in-service performance with statistical-based threshold reliability. The long history and the development of well-established analysis methods for structural design have bestowed on the civil engineering field the idea of being a hardly permeable sector to new approaches different from those well-established traditional physics-mathematical formulations. However, it is worth noting that over the decades, also approximated techniques have been established for tackling complex problems such as ones involving non-linearities issues.

Within this context, AI-based solutions can often provide valuable alternatives nowadays for efficiently solving new demanding problems and challenges in the Structural Engineering field. The ARTISTE Conference was founded to explore these new possibilities, in the direction of developing applications for future AI-based smart cities and smart infrastructures. This includes but is not limited to, computational intelligence and soft computing methods, such as evolutionary and metaheuristic algorithms for coping structural optimization tasks, including also neural networks, fuzzy systems, expert feed-forward informed systems, and so on. Machine Learning (ML) methods such as classification, regression, and reinforcement learning, provide the possibility to develop new unseen data-driven approaches.

The Conference aims to serve researchers, professionals, students, or even simply enthusiasts, and provide an overview of the most recent advances of AI applied in Structural Engineering applications. 

Timetable

The ARTISTE Conference takes place 14-17 September, 2025. Authors selected by the Guest Editors (see below) will be encouraged to submit to DCE when ready after the Conference, with a final deadline of 1 September 2026. Articles will be published as soon as possible after acceptance and included on a collection page dedicated to the Conference. 

How to Submit

Key considerations for submitting are below, with full details available in the DCE Instructions for Authors. Articles submitted to DCE are expected to be longer than the Conference proceedings published in Springer’s Lecture Notes in Civil Engineering and therefore at least 30% different to the Conference version. 

Article types

When they submit to DCE authors are given the following option of article types to select from:

• Research articles using data science methods and models for improving the reliability, resilience, safety, efficiency and usability of engineered systems.
• Translational papers demonstrating the downstream benefits of data-intensive engineering - and the underlying data science principles, techniques and technologies - to wider society, economy, environment, health and way of life. For some more detailed instructions, see this guide to translational papers.
• Data papers that describe in a structured way, with a narrative and accompanying metadata, important and re-usable data sets in open repositories with potential for re-use in engineering research and practice. These papers promote data transparency and data re-use.
• Survey papers providing a detailed, balanced and authoritative current account of the existing literature concerning data-intensive methods in a particular facet of engineering sciences.
• Tutorial reviews providing an introduction and overview of an important topic of relevance to the journal readership. The topic should be of relevance to both students and researchers who are new to the field as well as experts and provide a good introduction to the development of a subject, its current state and indications of future directions the field is expected to take

We anticipate that most articles deriving from ARTISTE will be submitted as research articles.

Templates

Authors have the option but are not required to use the following templates:

• DCE LaTeX template files
• Overleaf (a LaTeX-based collaborative authoring tool; read about benefits of this tool)
• DCE Word template

Note that authors should provide both an abstract that summarises the paper (250 words or less) and beneath it an impact statement (120 words describing the significance of the findings in language that can be understood by a wide audience). Competing interest, funding and data availability statements should be provided at the end of the main text above the references (see disclosure statements).

Articles should be submitted through the DCE ScholarOne Manuscripts system, but note that if you use the Overleaf tool you can submit directly into the system without having to reupload files. 

You should select the 'Artificial Intelligence in Structural Engineering' option in response to the question about special collections so that we can assign your submission accordingly.

Peer Review

Articles will go through the standard DCE peer review process and receive two reviews from reviewers with a mixture of engineering and data science expertise. 

Why Submit to DCE?

✔ A venue dedicated to the potential of data science for all areas of engineering.
✔ Welcoming research and translational articles from authors, whether they are based in academia or industry.
✔ Well-cited (2024 Impact Factor: 2.8; 2024 CiteScore: 4.4) and indexed in Web of Science, Scopus and Directory of Open Access Journals.
✔ #OpenAccess with support for unfunded authors thanks to the Lloyd's Register Foundation - no hard requirement to pay an article processing charge (APC).
✔ Promotes open sharing of data and code through Open Science Badges.

Open Access

Any author can publish on an open access basis in DCE if accepted, irrespective of their funding situation or institutional affiliation. There are no financial barriers to publication. Many articles are covered through the Transformative Agreements that Cambridge has set up with universities worldwide. If the corresponding author on an article is affiliated with a Transformative Agreement this effectively covers open access publishing costs. Authors not affiliated with these agreements who have grants that budget for open access publication are encouraged to pay an article processing charge (APC). However, if an author has no funding and no institutional agreement, the charge will be waived without question. DCE is supported by a grant from the Lloyd’s Register Foundation, which helps subsidise the publishing costs of unfunded authors.

Guest Editors

• Giuseppe Carlo Marano (Politecnico di Torino, Italy)
• Domenico Asprone (University of Naples, Italy)
• Xinzheng Lu (Tsinghua University, China)
• Nikos D. Lagaros (National Technical University of Athens, Greece)
• Eleni Chatzi (ETH Zurich, Switzerland)
• Marco Martino Rosso (Politecnico di Torino, Italy)
• Laura Sardone (Politecnico di Torino, Italy)
• Jonathan Melchiorre (Politecnico di Torino, Italy)