European Conference on EDGE AI Technologies and Applications - EEAI 2025

The European Conference on EDGE AI Technologies and Applications - EEAI 2025 explores the development, optimisation, and application of intelligent edge AI systems across hardware, software, and practical use cases.

Key Topics

• Generative edge AI
• Edge AI heterogeneous systems integration
• Energy-aware edge AI and power-adaptive inference
• Human-to-edge AI interaction and privacy
• Machine vision: image classification, object detection, semantic segmentation
• Transformers at the edge
• Compact and efficient generative architectures
• Federated learning
• Edge AI accelerators – GPUs, NPUs, TPUs, ASICs, FPGAs
• Safe, verifiable, explainable, interpretable AI for autonomous edge agents
• Optimisation methods for neural networks
• On-device modelling and predictive control
• Neuromorphic computing for ultra-low-power edge AI
• AI hardware-software co-design methods
• Compiler and firmware co-design for edge AI workloads
• Architectures, frameworks, and protocols for edge processing
• Benchmarking edge AI models
• Reconfigurable edge AI
• Advanced federated learning and swarm intelligence
• Agentic and embodied AI at the edge
• Edge AI explainability and interpretability
• RISC-V-based edge AI acceleration
• Multi-agent collaboration at the edge
• On-device continual learning
• Simulation and analysis techniques for edge intelligence
• Ethical implications of edge AI
• Ultra-low-bit quantization and binarization
• Smart connectivity at the edge
• Edge AI verification, validation, and testing
• Trustworthy edge AI systems
• Frameworks for generative and agentic edge AI
• Heterogeneous edge AI hardware integration
• Generative data augmentation for training
• Adversarial robustness and security for edge AI
• Sustainable edge AI technologies
• Edge AI auto ML
• Edge AI natural language processing and speech
• Immersive technologies with edge AI (XR/VR/AR/MR)
• Integrated hardware and software edge platforms
• Energy optimisation for edge devices
• Immersive experiences with real-time AI at the edge
• Edge AI workflows and systems design
• Edge-native reinforcement learning
• Neuromorphic hardware architectures
• Edge AI optimisation for 5G/6G
• Edge AI tools and methods

Who should Attend

• Industry practitioners
• Researchers
• Academics