Trends and Prospects in AI-Empowered Information Systems and Technologies
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 20 April 2025 | Viewed by 67
Special Issue Editors
Interests: computational intelligence; pattern recognition; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: computer education; artificial intelligence; software engineering
Interests: smart systems and software engineering for business and society; education technology
Special Issues, Collections and Topics in MDPI journals
Interests: decision support; decision making; big data; analytics; business intelligence
Interests: applied artificial intelligence; smart electric power systems and smart grids; machine learning in national security applications; artificial intelligence in smart cities; intelligent control methods in power systems; intelligent systems for signal processing and detection algorithms; machine learning and pattern recognition; nuclear security and nonproliferation; AI in radiation detection; AI in nuclear power applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Contemporary Information Systems and Technologies (ISTs) increasingly incorporate Artificial Intelligence (AI) technologies, enhancing their trustworthiness and robustness of autonomy and expanding their applicability across various new domains. These AI-empowered approaches prove to be very effective and include (1) intelligent systems in which expertise, knowledge, and AI are integrated; (2) support via tailored recommendations that provide personalized and group recommender systems; (3) dynamic support to address the complexities of limited and imbalanced data; (4) transparent and ethical support, ensuring explainability, privacy, data protection, trust, and responsibility; and (5) novel holistic software engineering development, verification and evaluation methodologies. By employing AI methodologies in knowledge-based software development, ISTs can effectively analyze vast datasets and extract valuable insights to support IST processes across diverse domains. Furthermore, this AI-driven enhancement extends the applicability of IST to novel domains as advancements in machine learning, deep learning, fuzzy logic and paradigm fusion technologies enable contemporary IST to support various industries and sectors. To efficiently develop and use AI-empowered ISTs, further research is required in the following topics:
- Incorporating AI enhancements into ISTs;
- Developing AI tools for engineering autonomous ISTs;
- Software engineering for AI technologies;
- Explainable, trustworthy, and responsible AI-empowered ISTs, including addressing privacy and security issues;
- Innovative applications of AI-empowered ISTs in various fields, including the energy, environment, medical, financial sector, management, education, and engineering disciplines.
This proposed SI addresses some of the most significant recent advances in AI-empowered ISTs. It is aimed at professors, researchers, scientists, engineers, and students in all computer science, AI, and IST disciplines. It is also directed towards readers from other disciplines interested in becoming versed in some of the most recent AI technologies as they empower IST.
Prof. Dr. George A. Tsihrintzis
Prof. Dr. Maria Virvou
Prof. Dr. Hironori Washizaki
Prof. Dr. Gloria Phillips-Wren
Dr. Miltiadis (Miltos) Alamaniotis
Guest Editors
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Keywords
- artificial intelligence
- machine learning
- deep learning
- fuzzy logic
- information system
- explainable artificial intelligence
- trustworthy and responsible artificial intelligence
- artificial intelligence-empowered system
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