Wouter Kouw

Wouter Kouw is a researcher in the Bayesian Intelligent Autonomous Systems lab of the Electrical Engineering department. He has a dual background in neuroscience and computer science, and is most interested in neuro-inspired forms of artificial intelligence. His research focuses on analyzing, designing and developing probabilistic machine learning systems based on models of information processing in the brain. Specifically, variational Bayesian inference algorithms implemented as message passing on factor graphs. His work has been applied to signal processing and control, with the latest projects moving towards mobile robotics. He is a former Niels Stensen Fellow and currently works part-time as a Research Associate at Sioux Technologies.

Nature has produced elegant forms of information processing that I believe can help us tackle challenges in modern society.