The investments we support and manage
Robotic platforms enabling a continuum
of caring for stroke patients from
clinics to home
Embedded systems, reimagined. Advanced digital twin for the electrical drive and the automation industry.
Energy storage system which unifies the advantages of high energy density cells (e.g. LiS) and high power density systems (e.g. supercapacitors) to overcome the existing limitation in energy storage
Microwave imaging (MWI) technology, enhanced by specific machine learning algorithms, to detect contaminants within packaged food/beverage products directly along the industrial production line.
Fog computing platform with innovative application-aware orchestration of infrastructure’ resources.
Portable (flexible, lightweight and low-voltage powered <10V) and large area (30 cm x 30 cm or more) direct radiation detectors.
Novel technology for non-invasive glycemia monitoring, based on a high-sensitivity Radio Frequency (RF) sensor, to retrieve glucose information from alternative corporal fluids, such as sweat, saliva or tears.
Water-soluble bioplastic with tunable temperature-dependent performances.
Smart texture enabling motion and gesture control real time. It would be used as working suites for collaborative robotics operations
Artificial Intelligence (AI) to the edge of the IOT: design tools that assist developers during the design flow of systems and applications, providing automated optimization for AI onto battery-powered tiny devices
BIOFIBER is a new generation of advanced highly absorbent medicated dressings, which features an innovative new fiber technology
ML-guided Directed Evolution, a novel machine learning method that uses a powerful ad-hoc modelization to obtain extremely accurate predictions for best protein candidate in Drug Discovery.
Use of recoverable sorbent materials to remove MOH from the cellulose suspension in paper mills, allowing to produce safer food packaging made of recycled cellulose.
A smart medical device on hospitals beds for accurate and continuous monitoring of urine output and early diagnosis of Acute Kidney Injury through machine learning algorithms