Special Session on dAIEDGE: Trustworthy, Regulated, and Efficient AI on the Edge (TRUST-E)

Scope

This Special Session focuses on advancing Artificial Intelligence at the edge by exploring theoretical, practical, and interdisciplinary perspectives. It will highlight recent progress, challenges, and innovations in Edge AI, including emerging software and hardware solutions, on-device learning, energy optimization, and communication strategies for resource-constrained devices.

Key topics include hybrid and distributed AI, energy-efficient architecture, and frameworks for Edge AI deployment. The session will also cover federated learning, privacy-preserving techniques, and the security of distributed edge  systems. This theme, along with other potentially related topics on the cybersecurity of edge AI, will be discussed.

Contributions discussing human rights, data protection, and other legal aspects of Artificial Intelligence at the edge, including interdisciplinary perspectives, are welcomed. Topics of interest include trustworthiness, non-discrimination and fairness, risk management, explainability, interpretability, human intervention, and more general data protection and security aspects.
 


Topics

This Special Session provides a collaborative platform discussing Artificial Intelligence at the edge, encompassing diverse perspectives on this theme and other potentially related topics:

  • Edge AI scientific progress
  • Emerging SW/HW approaches for edge AI
  • Datasets and testbeds
  • On-device communication
  • Energy efficiency and optimization
  • Hybrid and distributed AI solutions
  • Edge AI on-demand framework
  • Distributed edge AI marketplace
  • Architectures for energy efficiency in distributed AI systems
  • Code generation, tuning, and deployment for Edge AI system
  • Generative edge AI
  • Trustworthy edge AI
  • Edge AI explainability and interpretability
  • Legal and ethical aspects of edge AI
  • Federated learning
  • Sustainable AI Systems for Economic and Social Impact
  • AI Innovations for Economic Growth and Resilience
  • Sustainable AI Solutions for Environmental Impact

Contributions containing both theoretical and practical results are welcomed.
 

Organizing Committee

  • Javier Parra Domínguez, USAL
  • Ricardo S. Alonso, AIR Institute

Program Committee

  • Oscar Deniz, UCLM 
  • Ander García, VICOM 
  • Alain Pagani, DFKI 
  • Aysajan Abidin Cosic, KU Leuven 
  • Lydia Belkadi KU, Leuven 
  • Mohamed Selim, DFKI  
  • Irene González Pulido, USAL 
  • Vanessa Jiménez Serranía, USAL 
  • Philippe Massonet CETIC 
  • Pierre-Yves Danet, SCoDIHNet 
  • Giovanni De Gasperis, Univaq
  • Jack D. Márquez, UTK
  • Joao Neves, UBI
  • Pedro Inácio, UBI
  • Fatih Turkmen,RUG
  • José Alberto Benítez, ULE
  • Emiliano García Coso, UComillas
  • Jovanny Bedoya Guapacha, UTP    
  • Jonas Queiroz, UNESP
  • Marcela Herrera, UAO