Leader of the group Machine Learning: Peter Grünwald.

Our research group focuses on how computer programs can learn from and understand data, and then make useful predictions based on it. These algorithms integrate insights from various fields, including statistics, artificial intelligence and neuroscience.  

 Machine-learning applications are increasingly part of every aspect of life, from speech recognition on cell phones to illness prediction in healthcare. One common problem is extremely polluted data, for which no single model can provide adequate explanations. At CWI we address this issue with statistical machine learning based on combining predictions from different models and experts in order to achieve reliable conclusions.

We also study how networks of neurons in the brain process information, and how modern deep-learning methods can benefit from neuroscience. We develop novel neural networks, like Deep Adaptive Spiking Neural Networks, and also theoretical models of neural learning and information processing in biology. Applications of our work range from low-energy consumption neural machine learning to neuroprosthetics, to increased insight into the question of how the brain works.



No vacancies currently.


Current events

Neuromorphic Computing Netherlands (NCN2021)

  • 2021-09-24T12:50:00+02:00
  • 2021-09-24T18:00:00+02:00
September 24 Friday

Start: 2021-09-24 12:50:00+02:00 End: 2021-09-24 18:00:00+02:00

CWI, Euler room

Neuromorphic Computing is rapidly emerging as the principle paradigm for EdgeAI. In this workshop, we aim to bring together researchers and practitioners from algorithmic, architectural and application domains in the Netherlands.

When: 24 September, 12:50h-17:30h.
Location: CWI Amsterdam and online (hybrid).
Keynote: prof dr Elisabetta Chicca (RUG)

Zoom link:


12:50h Opening
13:00h Keynote by Elisabetta Chicca (RUG)
13:50h break
14:00h Federico Corradi (IMEC)
14:25h Jesse Hagenaars (TUD)
14:50h Mahyar Shahsavari (RU)
15:15h posters / break
16:00h Bojian Yin (CWI)
16:25h Thomas Tiotto (RUG)
16:50h drinks

This workshop is organized as part of the Efficient Deep Learning NWO-TTW Perspectief programme.



Associated Members



Current projects with external funding

  • Efficient Deep Learning Platforms (eDLP)
  • Enabling Personalized Interventions (EPI)
  • Human Brain Project - SGA3 (HBP-SGA3)
  • Efficient Models of Decision-Making for Asseing Cognitive Processing States (None)
  • Perceptive acting under uncertainty: safety solutions for autonomous systems (None)
  • Safe Bayesian Inference: A Theory of Misspecification based on Statistical Learning (SAFEBAYES)
  • Spiking Neural Networks research program

Related partners

  • Philips
  • KPMG
  • SURFsara B.V.
  • Technische Universiteit Eindhoven
  • Universiteit Twente
  • Universiteit van Amsterdam
  • Vrije Universiteit Amsterdam