Journal Information

Journal of Computational Science

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Impact Factor:
3.7
Publisher:
Elsevier
ISSN:
1877-7503
Viewed:
28088
Tracked:
10

Call For Papers

Journal of Computational Science is an academic journal published by Elsevier. (ISSN 1877-7503, impact factor 3.7).

Computational Science is a rapidly growing multi- and interdisciplinary field. It develops mathematical and computational models and uses advanced computing techniques to simulate these models, driven by data. Its overarching goal is to understand and solve complex problems. It has reached a level of predictive and interventional capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data-driven modeling and simulation which is no longer feasible using traditional analytical approaches alone. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments). The Journal of Computational Science aims to be an international platform to exchange novel research results in simulation-based science across all scientific disciplines. It publishes advanced innovative, interdisciplinary research where complex multi-scale, multi-domain problems in science and engineering are solved, integrating sophisticated numerical methods, computation, data, networks, and novel devices. The journal welcomes original, unpublished high quality contributions in the field of computational science at large, addressing one or more of the aforementioned elements.
Last updated by Dou Sun in

Special Issues

Special Issue on AI-Driven Computational Science for Sustainable and Societal Challenges: Methods, Models, and Real-World Applications Submission Date: 2026-06-09 This Special Issue explores the convergence of artificial intelligence and computational science to address critical sustainability and societal challenges. We focus on advanced computational methods applied to real world domains, spanning machine learning, data driven modeling, simulation and optimization in areas such as healthcare and biomedicine, renewable energy, waste management, cultural heritage preservation, intelligent transportation, smart cities and industrial production. We welcome both theoretical contributions that advance computational methodologies and practical studies that demonstrate their effective deployment in real-world scenarios. The issue encourages extended versions of selected best papers from IEEE BIBM 2025 and IEEE BigData 2025 workshops, along with a limited number of open submissions from the broader community. Unlike existing collections that examine isolated AI applications, this Special Issue positions computational science as the unifying methodological backbone for scalable, interpretable and transferable solutions across diverse real-world domains. We emphasize explainability, transparency, and ethical deployment in high-impact contexts where trust and accountability are essential. Guest editors: Prof. Ester Zumpano Università della Calabria, Rende, Italy Email: e.zumpano@dimes.unical.it Areas of Expertise:Artificial Intelligence; Computational Science; Database Systems; Real-World; Applications Prof. Luciano Caroprese University of G. d'Annunzio Chieti and Pescara, Chieti, Italy Email: luciano.caroprese@unich.it Areas of Expertise: Deep Learning; Logic Programming and Knowledge Representation; Recommender Systems; Data Integration Techniques and Deductive Databases; Neurosymbolic and Explainable AI; AI systems for medical applications PhD Eugenio Vocaturo Università della Calabria, Rende, Italy Email: ing.eugenio.vocaturo@gmail.com Areas of Expertise: Artificial Intelligence; Deep Learning; Explainable AI; Multiple Instance Learning; Medical Imaging; Sustainability Applications; Industrial Systems Dr. Tommaso Ruga Università della Calabria, Rende, Italy Email: tommaso.ruga@dimes.unical.it Areas of Expertise: Artificial Intelligence; Computational Science; Database Systems Dr. Maira Aracne Rectorate of Leonardo da Vinci Telematic University, Torrevecchia Teatina, Italy Email: m.aracne@unidav.it Areas of Expertise: Artificial Intelligence; Computational Science; Environmental Forecasting Special issue information: Full scope of the Special Issue: This Special Issue addresses the strategic integration of AI, computational science, and big data analytics for real-world sustainability and societal challenges. The unifying theme explores how computational methods, machine learning, modeling, simulation, and optimization, tackle real-world applications. We seek contributions that advance both the theoretical foundations and practical implementations of computational methods and models, bridging the gap between algorithmic innovation and real-world deployment.The issue welcomes extended versions of selected best papers from five workshops held at IEEE BIBM 2025 (Artificial Intelligence Techniques for BioMedicine and HealthCare, Large Language Models and Big Data Analytics for Health and Medicine, Diversity, Equity & Inclusion in HealthCare) and IEEE BigData 2025 (AI-Driven Applications in Real-Life Domains, AI-driven Agriculture: Opportunities and Challenges). Additionally, a limited number of open submissions are accepted from the broader computational science and AI communities for high-quality original research aligned with the Special Issue themes. Global sustainability challenges outlined in the European Green Deal and UN's 2030 Agenda demand innovative computational solutions transcending disciplinary boundaries, including digital twins for optimization, explainable AI for transparency, distributed computing for scalability, predictive modeling for forecasting, large language models for analytics, and computer vision for automation. Papers are expected to present novel methodological contributions alongside empirical validation in real-world scenarios. We particularly encourage submissions that demonstrate how theoretical computational advances translate into practical, deployable solutions. Special emphasis on explainability and ethical deployment ensures reproducibility in high-impact contexts, particularly in healthcare where patient safety and clinical decision support are critical. Through this perspective, the Special Issue aligns with Journal of Computational Science's mission of combining computational thinking with modern methods for complex problems beyond traditional numerical approaches. Manuscript submission information: Important Dates: Submission Deadline: 9 June 2026 Editorial Acceptance Deadline: 9 October 2026 Manuscripts must be submitted via the Journal of Computational Science online submission system (Editorial Manager®). Please select the article type “VSI: AI&CS4Social” when submitting your manuscript online. Please refer to the Guide for Authors to prepare your manuscript. For any further information, the authors may contact the Guest Editors. Keywords: Artificial Intelligence; Computational Science; Machine Learning; Sustainability Computing; Smart Cities; Renewable Energy; Waste Management; Cultural Heritage; Digital Twins; Explainable AI; High Performance Computing; Real-World Applications
Last updated by Dou Sun in

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