Guest Editor(s)
Prof. Dr. Biswajeet Pradhan
Email: biswajeet.pradhan@uts.edu.au
Affiliation: Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering & IT, University of Technology Sydney, Sydney, Australia
Homepage:
Research Interests: Geospatial Information Systems (GIS), remote sensing and image processing, complex modeling/geo-computing, machine learning, soft-computing applications, natural hazards and environmental modeling, remote sensing of Earth observation
Prof. Dr. Shilpa Bade
Email: shilpa.gite@dpu.edu.in
Affiliation: Department of Computer Science, Dr. D.Y. Patil School of Science & Technology, Pune, Maharashtra, India
Homepage:
Research Interests: deep learning, computer vision, multi-sensor data fusion, assistive driving
Summary
Recent advances in Generative Artificial Intelligence (GenAI), Large Language Models (LLMs), multimodal AI, vision-language models, foundation models, autonomous agents, and explainable AI are transforming the development of Intelligent Decision Support Systems (IDSS). These technologies are enabling adaptive, context-aware, and data-driven decision-making across diverse application domains by enhancing predictive analytics, knowledge generation, reasoning capabilities, and human-AI collaboration.
This Special Issue aims to bring together researchers, practitioners, and industry experts to present the latest advances in next-generation intelligent decision support systems powered by Generative AI. The issue seeks high-quality original research and review articles addressing theoretical developments, computational methodologies, computer vision and multimodal intelligence, system architectures, trustworthy AI frameworks, and real-world applications that improve decision intelligence and support complex decision-making processes.
Topics of interest include, but are not limited to:
· Large Language Models, Retrieval-Augmented Generation, Knowledge Graphs, and Neuro-Symbolic AI for Knowledge-Grounded Decision Support
· Multimodal Foundation Models, Vision-Language Models, and Visual Analytics for Complex Decision Intelligence
· Autonomous AI Agents, Copilots, and Workflow Automation for Decision-Making
· Explainable, Trustworthy, Secure, and Privacy-Preserving GenAI-Enabled Decision Frameworks
· Human-AI Collaboration and Augmented Decision Intelligence
· Predictive, Prescriptive, and Generative Analytics, Combined with Reinforcement Learning and Adaptive Optimization for Dynamic Decision Support
· Federated, Edge, and Distributed AI, Digital Twins, and IoT Platforms for Domain-Specific Decision Support
We welcome submissions that contribute to the theoretical foundations, methodologies, algorithms, large language models, computer vision systems, multimodal foundation models, architectures, and practical applications of Generative AI-enabled decision support systems. Both original research articles and comprehensive review papers are encouraged.
Keywords
large language models (LLMs), decision support systems, generative AI, retrieval-augmented generation (RAG), AI agents, explainable AI (XAI)
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