All research, education, community building and collaboration activities will take place at the Alliance Artificial Intelligence Hub (AI-Hub).

In order to strengthen the implementation of trustworthy and explainable AI as enabling technology for preventive health and circular society, we will facilitate partnerships with the two respective institutes of EWUU – the Institute for Preventive Health and the Institute for Circular Society – to make sure that AI is applied in these domains in alignment with their research goals.

The core research theme is AI as enabling technology that revolutionizes the way we do science: Scientific discovery through trustworthy AI. The other main themes are the two societal impact domains that connect with Preventive Health and Circular Society.

Impact

Collaboration between all alliance partners is pursued in four aspects within the core research line, which can be seen as basic research on AI building blocks which form the preconditions for implementing AI in the societal impact domains. The four building blocks are:

• Data quality and accessibility
• Trustworthy and explainable AI
• Ethical, legal and societal aspects of AI
• empowering scientific discovery through AI

Objectives of the AI hub

• Perform research to foster scientific discovery through trustworthy AI.
• Establish insights where AI can support and contribute to breakthrough developments within the alliance.
• Connect the projects in the hub with the existing AI Labs of the alliance partners.
• Collaborate with Preventive Health and Circular Society to (co-)fund projects in the two societal impact domains.
• Scout national (and if possible, international) funding opportunities and involve researchers in consortium building events; capitalize on the emerging research collaborations within the alliance.

Our research lines:

• Scientific discovery through trustworthy AI
• Smart Healthcare and Prevention
• AI-driven healthy and sustainable ecosystem

AI-hub projects:

Scientific Discovery through trustworthy AI:

• AI aided knowledge discovery
  Team: Rens van de Schoot (UU), Daniel Oberski (UMCU), Ricardo Torres (WUR), Virag Sihag, Chris Knighting (TU/e)
• Ethical, Legal and Societal aspects of AI: ELSA lab proposal
  Team: Karin Jongsma (UMCU), Leendert van Maanen, Nadya Purtova (UU), Martijn Willemsen, Panos Markopoulos (TU/e), Annemarie Wagemakers (WUR), Patiëntenfederatie
• Algorithms for explainable AI
  Team: Maarten van Smeden (UMCU), Anna Vilanova Bartoli (TU/e)

Societal impact domains (preventive health and circular society):

• Dissemination of remote patient monitoring and wearables in the context of the “juiste zorg op de juiste plek”
  Team: Pieter van Gorp (TU/e), Teus Kappen (UMCU), Martine Breteler (UMCU)
• The personalization of medicine by machine learning for image interpretation
  Team: Nico van den Berg (UMCU), Mitko Veta (TUe), Josien Pluim (TU/e)
• Deep learning on multimodal inputs (video, sensors) with use case: individual feeding behaviour from consumption data
  Team: Ricardo Torres (WUR), Guido Camps (WUR), Albert Salah (UU)