Projects

Effective personalized medicine for paediatric cancers must address a multitude of challenges, including domain-specific challenges. To overcome these challenges, we propose a comprehensive computational effort to combine knowledge-base, machine-learning, and mechanistic models to predict optimal standard and experimental therapies for each child. Our approach is based on...

Health scientific discovery and innovation are expected to quickly move forward under the so called fourth paradigm ofscience , which relies on unifying the traditionally separated and heterogeneous high-performance computing and big dataanalytics environments. Under this paradigm, the DeepHealth project will provide HPC computing power at the service of biomedical...

We propose to create the EUropean-CANadian Cancer network (EUCANCan), a federated infrastructure whose mission is to enable Personalized Medicine in Oncology by promoting the generation and sharing of harmonized genomic and phenotypic data. EUCANCan builds on work performed by members of the consortium and related projects to align and interconnect existing European and...

At an increasing rate, industrial and scientific institutions need to deal with massive data flows streaming in from a multitude of sources. For instance, maritime surveillance applications combine high-velocity data streams, including vessel position signals emitted from hundreds of thousands of vessels across the world and acoustic signals of autonomous, unmanned vessels;...

Artificial Intelligence is a disruptive technology of our time with expected impacts that rival those of electricity or printing. Resources for innovation are currently dominated by giant tech companies in North America and China. To ensure European independence and leadership, it is important to invest wisely by bundling, connecting and opening European AI resources.