Explainable Artificial Intelligence for Engineering Projects
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Evolutionary Algorithms and Machine Learning".
Deadline for manuscript submissions: 15 August 2026 | Viewed by 99
Special Issue Editor
Interests: AI-driven data integration; explainable & human-centric AI; knowledge representation & reasoning; systems engineering; EdTech
Special Issue Information
Dear Colleagues,
The rapid integration of artificial intelligence (AI) into engineering, project management, and industrial systems is fundamentally transforming how complex decisions are designed, justified, and executed. Beyond performance and automation, contemporary AI solutions are increasingly expected to be transparent, trustworthy, and aligned with human values and organizational objectives.
This Special Issue aims to explore explainable, hybrid, and human-centric AI approaches that support decision-making, risk management, and system optimization in engineering and industrial contexts. Particular attention is given to methods that combine data-driven models (machine learning, deep learning, and large language models) with structured knowledge representations, domain expertise, and reasoning mechanisms, enabling more interpretable, auditable, and robust AI systems.
The Special Issue welcomes original research and high-quality review papers addressing theoretical advances, applied frameworks, and real-world case studies related to AI-enabled decision support, intelligent data integration, project and risk analytics, and engineering systems management. Contributions that bridge academic research with industrial practice, sustainability objectives, and digital transformation challenges are especially encouraged.
Topics of interest include, but are not limited to, the following:
- Explainable AI and interpretable machine learning for engineering applications;
- Hybrid AI systems;
- Knowledge graphs, ontologies, and structured knowledge for decision support;
- AI-based risk prediction, assessment, and mitigation in projects and systems;
- Human-centric and trustworthy AI in industrial and organizational settings;
- AI-driven decision support systems for engineering management and sustainability;
- Integration of large language models into enterprise and engineering workflows.
This Special Issue seeks to provide a multidisciplinary forum for researchers and practitioners interested in advancing responsible, transparent, and effective AI solutions for complex engineering and management problems.
Dr. Maria-Iuliana Dascalu
Guest Editor
Manuscript Submission Information
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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. Algorithms is an international peer-reviewed open access monthly 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 1800 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
- explainable artificial intelligence (XAI)
- hybrid AI systems
- knowledge representation
- decision support systems
- engineering management project and risk
- analytics human-centric
- AI intelligent information systems
- trustworthy AI digital transformation
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