Machine Learning and Artificial Intelligence in Modelling
A special issue of Modelling (ISSN 2673-3951).
Deadline for manuscript submissions: 31 March 2026 | Viewed by 15
Special Issue Editors
Interests: artificial intelligence; machine learning; neural networks; deep learning; fuzzy logic
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, Machine Learning (ML) and Artificial Intelligence (AI) have radically transformed how we build, validate, and apply models across science, engineering, and industry. These technologies offer powerful methods for capturing nonlinear dependencies, learning from heterogeneous and high-dimensional data, and modelling complex dynamic systems where traditional mathematical approaches often fall short.
This Special Issue aims to gather original research articles and reviews focused on the application of modern ML and AI methods in the context of engineering modelling and simulation. We welcome contributions on hybrid approaches that integrate domain knowledge with learning algorithms, interpretable models, and physics-informed machine learning techniques. In addition, the Special Issue is open to a broad spectrum of topics, including but not limited to:
- Automated modelling and AutoML
- Modelling with limited data and transfer learning
- Explainable and trustworthy AI models
- Probabilistic and Bayesian modelling
- Spatio-temporal AI and time-dependent models
- Multimodal modelling (e.g., combining text, images, sensors)
- Neuro-symbolic and symbolic modelling approaches
- Meta-modelling and higher-order model composition
- AI-accelerated simulation and surrogate modelling
- Embedded models and edge AI for real-time systems
The Special Issue encourages interdisciplinary contributions that demonstrate methodological innovation or application-driven insight within the scope of engineering sciences. Our goal is to foster a platform for knowledge exchange on the next generation of intelligent modelling paradigms that are shaping the future of engineering.
Dr. Margarita Terzyiska
Dr. Miroslava Ivanova
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. Modelling is an international peer-reviewed open access quarterly 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 1000 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
- artificial intelligence
- hybrid modelling
- physics-informed machine learning
- interpretable AI
- AutoML and automated modelling
- bayesian and probabilistic modelling
- spatio-temporal models
- edge AI and real-time systems
- multimodal data fusion
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