Artificial Intelligence and Data-Driven Methods for Intelligent Systems and Applications

Dear Colleagues,

The rapid advancement of artificial intelligence (AI) and data-driven technologies is reshaping intelligent systems across business, scientific, and societal domains. While recent progress in machine learning, large language models (LLMs), generative AI, and data analytics has enabled unprecedented capabilities, significant challenges remain in developing intelligent systems that are reliable, explainable, scalable, and capable of integrating heterogeneous knowledge and data sources. Addressing these challenges requires rigorous mathematical foundations, advanced computational methods, and effective data-driven approaches.

This Special Issue focuses on the mathematical and computational principles underlying AI-enabled intelligent systems and their practical deployment in real-world applications. It aims to provide a forum for innovative research that advances the theory, methodology, and implementation of intelligent systems through data-driven modeling, optimization, learning, and knowledge integration. Particular emphasis is placed on research that bridges methodological advances with application domains while maintaining strong mathematical, algorithmic, or computational contributions.

The Special Issue welcomes original contributions in the following interconnected themes:

Theme 1: Learning, Reasoning, and Generative Intelligence

• Machine learning and deep learning methodologies;
• Large language models, foundation models, and generative AI;
• AI reasoning, explainability, robustness, and trustworthiness;
• Evaluation frameworks and benchmarking methodologies for AI systems.

Theme 2: Data, Knowledge, and Intelligent Decision Making

• Data management, data quality, and data analytics;
• Knowledge graphs, semantic technologies, and knowledge integration;
• Retrieval-augmented generation (RAG) and hybrid neuro-symbolic approaches;
• Recommender systems and intelligent decision-support techniques.

Theme 3: Mathematical and Computational Foundations for Intelligent Systems

• Optimization methods for machine learning and AI;
• Computational models and algorithms for intelligent systems;
• Scalable AI architectures and data-intensive computing;
• Theoretical analysis of learning, reasoning, and intelligent decision processes.

Theme 4: Intelligent Applications and Digital Systems

• Intelligent e-business and digital commerce systems;
• Business intelligence and data-driven services;
• Smart digital platforms and information systems;
• Emerging AI-enabled applications with demonstrated societal or industrial impact.

This Special Issue welcomes extended versions of selected papers from the 22nd IEEE International Conference on E-Business Engineering (ICEBE 2026) as well as high-quality submissions from the broader international research community. All submissions will undergo the journal’s standard peer-review process and should demonstrate significant original contributions in theory, methodology, computation, or application.

Prof. Dr. Rui Zhang
Dr. Jianzhong Qi
Prof. Dr. Xiang Ao
Prof. Dr. Yuanchun Jiang
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics 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 2600 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.