Total project budget of over 87 million, including 17 new labs and 170 new PhD candidates over 10 years
ROBUST, a new initiative by the Innovation Center for Artificial Intelligence (ICAI), is supported by the University of Amsterdam and 51 partners, one of them being the University of Twente. The programme aims to strengthen the Dutch artificial intelligence (AI) ecosystem by boosting fundamental AI research. Within the programme, UT will collaborate in the areas of data analytics for SMEs, energy transition and healthcare.
The additional €25 million grant comes from a call by the research council for Long-Term Programmes, which gives strong, public-private consortia the chance to receive funding for a ten-year period. Next to the research council, companies, and knowledge institutes contribute to the programme. The total ROBUST budget amounts to €87.3 million, of which 7.5 million comes from the Ministry of Economics and Climate. The ROBUST programme will shape the collaboration on dissemination, consolidation and valorisation of the results, as well as retaining talent in the Netherlands. This contributes to the ambitions of the Strategy Digital Economy of the cabinet to be at the forefront of human-centred AI development and AI applications.
Startups, SMEs, and policymakers
‘AI is a systemic technology that touches all aspects of society. That's why it's important to ensure that the application of AI technology becomes a widely shared responsibility. ROBUST collaborates with regional civil-social partners throughout the Netherlands, and especially with startups and small to medium-sized enterprises (SMEs)’, says De Rijke, programme leader of ROBUST. The objective is not only to develop knowledge and innovations with ROBUST partners but also to make them more widely available to other parties within the Dutch ecosystem. New findings and their policy implications will also be shared with national and European policymakers.
Role for University of Twente
The University of Twente plays an important role in the programme in three different labs: MKB Data lab Oost-Nederland, AI for Energy Grids and Healthy AI.
MKB Data lab East Netherlands
To make knowledge and innovation more widely available, ROBUST's efforts include seven SME Data Labs. The aim is to help regional SMEs make better use of artificial intelligence and get more value from their data. The SME data lab Oost-Nederland is a collaboration between the University of Twente and Radboud University. Starting from an intake, SMEs and the universities work towards a proposal for a customised assignment. This assignment is preferably carried out by a student under the guidance of an experienced project leader and has a scope of about 80 hours. This supports the entrepreneur to take the next step in a data-driven way of working.
AI for Energy Grids
The AI for Energy Grids Lab is a joint initiative of University of Twente, Alliander, TU Delft, Radboud University and Hogeschool Arnhem-Nijmegen. Within this lab, over the next five years, research will be conducted on innovative and urgent topics within the energy sector such as the ongoing energy transition or the electricity grid of the future. The lab combines the latest developments in AI with ongoing research on new concepts within the energy sector. This approach in combination with academic and industrial cooperation makes the lab a unique and promising direction towards impactful innovations within the energy transition. These innovations can then be directly applied to solve the challenges seen in distribution networks to enable the integration of more renewable energy and to support electrification.
How can we develop trustworthy, robust AI methods that can improve the quality of care, reduce healthcare costs, and reallocate time for routine decision-making to human-centric care in the domain of prostate cancer diagnosis? The lab Healthy AI is a collaboration between the University of Twente, Radboud UMC, Siemens Healthineers en UMC Groningen and will pursue five key tasks in this domain: (i) medical imaging and analysis, (ii) pathway analysis, (iii) generalization, (iv) long-term surveillance, and (v) image acquisition. Clinically validated advances in each of these tasks will improve the adoption of AI as an assistive technology in healthcare.
For more information about the SME data Oost-Nederland or the ICAI labs AI for Energy Grids or Healthy AI, please contact Anne Bergen (Impact Development Manager, UT).