22 October 2026

University of Amsterdam

Amsterdam UMC

Ten researchers from UvA and Amsterdam UMC receive Vidi grants, including four projects involving AI

How does AI reason, how do people adapt to algorithms, and can AI predict kidney disease? Four new Vidi projects set out to find out.

NWO is awarding a Vidi grant to ten researchers from the University of Amsterdam (UvA) and Amsterdam UMC. The grant is worth up to 850,000 euros and allows them to develop their own line of research and to set up or expand a research group. In total, NWO is awarding 109 Vidi grants in this round. Four of the funded projects revolve around AI.

  1. Dr. Vlad Niculae (Informatics Institute) is developing reliable language models in RECONSTRUCT that reason via a compact, hierarchical plan, inspired by concept maps. Currently, their thinking process can become long and chaotic, which makes AI too unreliable for high-stakes applications.
  2. Dr. Fernando Pascoal dos Santos (Informatics Institute) studies how people adapt to transparent algorithms in areas such as fraud detection, content moderation and recruitment, and develops tools that encourage prosocial adaptation, so that AI can be both transparent and robust.
  3. Dr. Sandro Pezzelle (Institute for Logic, Language and Computation) tests in multiple languages how well AI models link everyday remarks such as “unbelievable” to events in video, and then refines their inner workings for more reliable and explainable video AI.
  4. Dr. Rik Westland (Amsterdam UMC) combines laboratory techniques, imaging and artificial intelligence in MODERNART to capture the molecular features of congenital kidney diseases, aiming for more targeted prediction and treatment for children with these conditions, the cause of kidney failure in more than half of the children and young adults who develop it.

The other six grants go to research on topics including educational inequality, depression treatment, the consequences of crime, black rot in cabbage, citizens who avoid the government, and electrically switchable friction for chip production.

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