Jaume Abella Ferrer

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REBECCA, a heavily SME-driven project, will democratize the development of novel edge AI systems. Towards this aim, REBECCA will develop a purely European complete Hardware (HW) and Software (SW) stack around a RISC-V CPU, which will provide significantly higher levels of a) performance (e.g., inferences per second), b) energy/power efficiency (e.g., inferences per...

Deep Learning (DL) techniques are key for most future advanced software functions in Critical Autonomous AI-based Systems (CAIS) in cars, trains and satellites. Hence, those CAIS industries depend on their ability to design, implement, qualify, and certify DL-basedsoftware products under bounded effort/cost.There is a fundamental gap between Functional Safety (FUSA)...

The growing need to transfer massive amounts of data among multitudes of interconnected devices for e.g., self-driving vehicles, IoTor industry 4.0 has led to a quest towards low-power and secure approaches to locally processing data. Neuromorphic computing, a brain-inspired approach, addresses this need by radically changing the processing of information. Although...

The objective of this research activity is to create a reliable computing node that will create a Cognitive Edge under industry standards. This computing node will be the building block of scalable Internet of Things (from Low Computing to High Computing Edge Nodes). The cognitive skill will be given by an internal and external architecture that allows to forecast its...

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