Mathematical and Computer Modelling of Technical and Engineering Systems

Dear Colleagues,

In recent years, modelling has become an indispensable tool for understanding, predicting, and optimizing the behaviour of complex systems across science, engineering, and society. The rapid growth of computational power, coupled with advances in data-driven techniques such as machine learning and artificial intelligence, has opened up new frontiers for integrating theory, simulation, and real-world applications. These developments are transforming how researchers approach challenges ranging from industrial design and environmental sustainability to healthcare, transportation, and digital infrastructure.

This Special Issue will bring together cutting-edge research that highlights both methodological innovations and practical applications of modelling. We welcome contributions that explore novel mathematical frameworks, hybrid approaches combining physics-based and data-driven models, and interdisciplinary studies that bridge theory with practice. Particular emphasis will be placed on works that demonstrate how modelling can provide actionable insights, improve decision-making, and enhance system resilience in uncertain and dynamic environments.

By fostering collaboration among scholars worldwide, this Special Issue will create a cohesive collection of high-quality research articles and reviews that reflect the state of the art in modelling. Our goal is not only to showcase technical advances but also to stimulate dialogue across disciplines, encouraging the development of new ideas and future research directions. We invite contributions from both established experts and emerging researchers, and we strongly encourage collaborative submissions that span multiple domains of application.

Special Issue is open to a broad spectrum of topics, including but not limited to the following:

• Frontiers in Data-Driven and Computational Modelling of Complex Systems;
• Innovations in Computational and AI-Enhanced Modelling for Complex Systems;
• Hybrid Approaches in Data-Driven and Physics-Based Modelling of Complex Systems;
• Next-Generation Computational Modelling: From Algorithms to Applications.

Through this Special Issue, we will provide a platform for advancing the science and practice of modelling, while building a global community of researchers dedicated to pushing the boundaries of what modelling can achieve.

Prof. Dr. Pavlo Maruschak
Prof. Dr. Andrii Sverstiuk
Prof. Dr. Sergiy Yakovlev
Dr. Dmytro Chumachenko
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. Modelling 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 1200 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.