Group Leader
CurrentLeading the Learning Machines group, shared between the autonomous matter and information in matter research themes at AMOLF. My research efforts focus on the physics of learning in natural and synthetic systems. Such learning machines can adopt desirable properties and functions given real world examples and environments. Leveraging the advances of statistical learning theory in physical machines, physical learning is a promising bridge between computational machine learning and biology, and enables the development of new classes of bio-inspired smart metamaterials that adapt in-situ to users’ needs.