Towards an Understanding of Artificial Intelligence: Bridging Theory, Explainability, and Practical Applications

Scope

Artificial Intelligence (AI) has evolved rapidly, impacting various fields from healthcare to autonomous systems. However, as AI models become increasingly complex, understanding their decision-making processes is crucial for trust, fairness and applicability in practice. This special session aims to explore cutting-edge advancements in Explainable AI (XAI), Federated Learning, Trustworthy AI, Light-Weighted Edge computing, and Multimodal Large Language Models (LLMs), with a focus on time-series analysis, sensor fusion, generative models, and cyber-physical systems. Topics are as follows, but not limited to:

• XAI in Advanced Time Series and Visual Analysis
• XAI for Collaborative Sensor Fusion
• Federated Learning in Generative Models and Graph Neural Networks
• Sustainable and Trustworthy AI Solutions for Safety-Critical Cyber-Physical Systems
• LLM/VLM Theoretical and Applicable Developments
• Real-Time Anomaly Detection on Edge Devices
• Federated Learning with Heterogeneous Edge Nodes

This project is partially supported by the European Union’s HORIZON TMA MSCA Doctoral Networks, HORIZON-MSCA-2023-DN-01, grant number: 101168344

Important Dates

• Electronic submission of full papers: Oct. 30, 2026
• Notification of paper acceptance: Nov. 10, 2026
• Camera-ready of accepted papers: Nov. 14, 2026
• Conference: Dec 14-17, 2026

Organizers

• Rafal Cupek, Silesian University of Technology, Poland
• Dariusz Mrozek, Silesian University of Technology, Poland
• Jerry Chun-Wei Lin, Silesian University of Technology, Poland