eFficient decentRAlized proCessing of high-velociTy streamIng data spread across heterogeneous persONal data vaults

Efficient and scalable cascading reasoning over heterogeneous IoT data streams to enable real-time edge analytics

Explainable, human-in-the-loop hybrid AI, resolving conflicting user feedback

Behavioral change Interventions Made PERsonal, engagIng & lOng-term

Enabling personalized medicine by optimizing disease treatments with hybrid machine learning

FRACTION: eFficient semantics-pReserving And deCenTralized processIng of Big Data spread across persONal data vaults

Enhancing data analytics for IoT by enabling semantic enrichment of machine learning tasks

Cascading Reasoning: an Efficient and Scalable Solution for Decision Making on Heterogeneous Data Streams

Enhanced adaptive anomaly detection and root cause analysis by means of semantics and machine learning

A comprehensible and performant Decision Support System for longitudinal big data

Study and design of a federated, context-aware and self-learning reasoning framework enabling scalable and efficient advanced semantic reasoning on IoT data streams

Promoting stable remission in depression by combining e-health and cognitive science: the development of DEpression’s DIgital foreCAsting Tool (DEDICAT)

Explainable, human-in-the-loop hybrid AI, resolving conflicting user feedback and in a federated learning setting