Wouter Kouw develops probabilistic machine learning systems, particularly active inference agents, for autonomous robots. By formulating Bayesian inference as message passing on graphical models, he builds hierarchical reactive agents that learn internal kinematics and adapt to uncertain dynamic environments. These agents are deployed on mobile robots to automate hazardous tasks, creating safer work environments for people.

“Intelligence is more than just computation at scale - it’s about making sense of the world under uncertainty.”