ENEXA is an H2020 HUMAN project aiming at developing scalable, transparent and explainable machine learning algorithms for knowledge graphs, while maintaining their completeness and correctness.
EVENFLOW is an H2020 HUMAN project aiming at developing hybrid learning techniques for complex event forecasting, which combine deep learning with logic-based learning and reasoning into neuro-symbolic forecasting models.
CREXDATA is an H2020 DATA project whose vision is to develop a generic platform for real-time critical situation management, including flexible action planning and agile decision making over streaming data of extreme scale and complexity, using federated predictive analytics and forecasting under uncertainty algorithms.
VesselAI (2021-2024) aims at realising a holistic, AI-empowered framework for simulating and predicting vessel behaviour and manoeuvring, ship energy design optimisation, autonomous shipping and fleet intelligence.
ARIADNE (2019-2022) is a H2020 project bringing together a novel high-frequency radio architecture, and an Artificial Intelligence network processing and management approach, in order to allow for continuous reliable High Bandwidth connections in the Beyond 5G era.
INFORE (2019-2021) is a H2020 project that aims to address the challenges posed by huge datasets and pave the way for real-time, interactive, extreme-scale analytics and forecasting.
Track & Know (2018-2020) is a H2020 project with a mission to research, develop and exploit a new software framework for increasing the efficiency of Big Data applications in the transport, mobility, motor insurance and health sectors.
datACRON (2016-2019) was a H2020 project that introduced novel methods for detecting threats and abnormal activity in very large numbers of moving entities, operating in large geographic areas.
SPEEDD (2014-2017) was a FP7 European project that developed a prototype for proactive event-driven decision-making: decisions were triggered by forecasting events-whether they correspond to problems or opportunities-instead of reacting to them once they happen.
