Research Pillars

Adaptative AI

The Adaptive AI pillar focuses on enhancing the adaptability, efficiency, and reliability of AI systems in dynamic real-world environments by developing and accessing methods and algorithms for adaptive AI at the edge, as well as for robustness and trustworthiness in such environments. It draws inspiration from the brain to study the adaptation of AI systems. 

Research Areas
Topics
Projects from Open Calls
Project: Improving Edge AI Performance by Federation and Adaptive Model Selection 
Project: SHACKLE: SHape-based pAtterns for Constraining KnowLedge graph Embeddings   
Project: Adaptive Intelligence in Multi-Agent Systems: When Collective meets DRL  
Project: CXAI: Cautious explainable artificial intelligence  
Project: Robust Multimodal Continual Learning for Robotics