Projects

FAIRe_RIC – Frugal Artificial Intelligence in Resource-limited environments

FAIRe aims to develop resource-limited AI for embedded systems, cyber-physical systems, and edge devices. The development approach should extend …

BERTHA – BEhavioural Replication of Human drivers for CCAM

The Horizon Europe project BERTHA kicked off on November 22nd-24th in Valencia, Spain. The project has been granted €7,981,799.50 from the European …

MOMENTUM – Robust Learning with Hybrid AI for Trustworthy Interaction of Humans and Machines in Complex Environments

MOMENTUM is a research project dedicated to TRUSTED-AI, which aims to advance the development and application of artificial intelligence by …

Adra-e – AI, Data and Robotics ecosystem

Adra-e - Supporting the AI, Data and Robotics Community in the Development of a Sustainable European Ecosystem Adra-e is a Coordination and Support …

Open6GHub – 6G for Society and Sustainability

The project "Open6GHub" develops a 6G vision for sovereign citizens in a hyper-connected world from 2030. The aim of the Open6GHub is to provide …

STAR – Safe and Trusted Human Centric ARtificial Intelligence in Future Manufacturing Lines

STAR is a joint effort of AI and digital manufacturing experts towards enabling the deployment of standard-based secure, safe and reliable …

CLAIRE Saarland II – The CLAIRE Saarland Project

In June 2018, the CLAIRE initiative was launched with the aim of joining forces in the field of Artificial Intelligence in Europe with a focus on …

TAILOR – Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization

The TAILOR project was selected by the European Commission in the ICT-48-2020 call for proposals "Towards a vibrant European network of AI excellence …

CAMELOT – Continuous Adaptive Machine-Learning of Transfer of Control Situations

A remaining major challenge with autonomous systems is the handling of situations that the system cannot handle on its own. Up to now, this transfer …

Fast&Slow – Combination of Symbolic and Subsymbolic Methods

Deep learning methods are used in many application areas and work very efficiently after a training phase. However, in general no reliable statement …