Projects
The main objective of our project, KOIOS, is to develop new AI-based methods that are trustworthy (under human control and explainable), robust (resilient to attacks) and frugal in the use of resources (data, computing capabilities, energy,& ) addressing tasks in a more efficient manner than the current state-of-the-art ML/DL methods while...
The high-performance demands of the functionalities required in complex critical systems is rapidly increasing. In the space domain, on-board processing algorithms for navigation and control systems are needed to increase spacecraft autonomy; in the automotive and railway domains, advanced driving assistance systems (ADAS) and obstacle detection and avoidancesystems...
The overall aim of the EDITH project is to foster an inclusive ecosystem for Digital Twins in healthcare in Europe and to prompt the convergence of such an ecosystem towards a common strategy conducive to its further development. This is achieved by mapping and analysing the status of the fields which are crucial for the growth, uptake and use of digital twins in healthcare,...
The project proposes a solution for making on-demand configurable digital twin engines for forecasting of environmental extremes at the sub-km scale. We name the solution Destination Earth On-Demand Extremes (DEODE). The core of our solution is to provide an on-demand workflow with co-design of high resolution predictions about extreme weather events combined with decision...
The radical transformation of transport systems so they provide sustainable, clean, safe and integrated mobility is a major policy goal at nationaland European level. A major part of this effort aims to provide enhanced mobility experience to all users and improve the efficiency and safety of the transport network. Furthermore, the transport sector has a significant...
New certified designs for aircraft structures are critical for the upcoming changes in the conception of aircraft architectures. Various breakthrough designs and new strategies for better use of material and integration of functions in aircraft are required. They range from regional electrical mobility solutions to increase aspect ratio wings that will bring higher structure...
The unstoppable proliferation of novel computing and sensing device technologies, and the ever-growing demand for data-intensive applications in the edge and cloud, are driving a paradigm shift in computing around the dynamic, intelligent and yet seamless interconnection of IoT, edge and cloud resources in one single computing system to form a continuum. Many research...
Deep learning (DL) is widely used to solve classification problems previously unchallenged, such as face recognition, and presents clear use cases for privacy requirements. Homomorphic encryption (HE) enables operations upon encrypted data, at the expense of vast data size increase. RAM sizes currently limit the use of HE on DL to severely reduced use cases. Recently emerged...
CAELESTIS will develop an end-to-end Interoperable Simulation Ecosystem (ISE) that will perform multidirectional dataflow across the aircraftvalue chain linking product design and distributed engineering teams´ CAD-CAE tools, to accelerate the design and engineering optimization of disruptive aircraft and engine configurations, ensuring their manufacturability from the...
Ultrasound imaging can be deeply enhanced by means of algorithms developed in the field of geophysical imaging. Such algorithms, based upon adjoint-state modelling and iterative optimization, provide quantitative images of human tissue with very high resolution. At present time, suchimages can only be attained by means of high-performance computing and using specific...