The award of a Take-off grant is often the prelude to a spin-off. The five Radboud projects awarded this time are not only from the STEM and medical fields; there is also an award for an innovation in the social sciences (Yvonne van den Berg's Stoeltjesdans project).
In the autumn 2022 round, in which a total of 47 projects have been granted, the following Radboud projects were honoured:
Stoeltjesdans - Yvonne van den Berg
De Stoeltjesdans is a free, online tool that supports teachers in monitoring and managing the social safety at school. A first bètaversion was launched in 2016 and quickly grew to the unexpectedly high number of almost 14.000 users. However, it succumbs her success, due to the still growing (inter)national demands in combination with lack of financial and human resources. The goal of this project is therefore to test the feasibility of a commercialized and improved version of De Stoeltjesdans, that will be run by a new start-up. All to ensure the social safety of our children at school.
PiCard – quantum information hardware – Britta Redlich
PiCard Systems is a start up focusing on developing quantum hardware that provides infrastructure support for quantum computing, and its first device to do this will be the πcard. Quantum computing is a rapidly maturing field, which as yet does not have complimentary supporting hardware infrastructure, such as storage. Changing this means tackling complex problems. The πcard aims to explore this need using a unique combination of silicon technology, FIR optics and cryogenics.
New trans-cyclooctenes for diagnostic tests– Floris Rutjes
The aim of this project is to develop new diagnostic tests based on a smart click reaction using reactive trans-cyclooctenes. The trick of this reaction is that the conjugation of two molecules in this case leads to the release of another moclecule, which enables a new window of diagnostic applications.
Development of glycotherapeutics – Thomas Boltje
Every human cell is coated with carbohydrate structures called glycans. Many cancers overexpress certain glycans which is associated with their aggressiveness and invasiveness. In this project we investigate if targeting these glycans has therapeutic potential. By doing so, we could potentially severely cripple the cancer's ability to grow and metastasize.
Constence – Marcel van Gerven
Current AI systems consume an enormous amount of energy while learning new tasks as this learning takes place on large central computing clusters. The aim of this project is to show how new brain-inspired algorithms can enable us to make this learning more efficient and to apply it in embedded systems that do not use central compute clusters. This technique makes it possible to train AI systems in a more energy-efficient way and to enable learning in situations where one cannot or does not want to use central computing clusters.