On August 1st Menachem (Nachi) Stern will start as tenure track group leader at AMOLF. He will lead the Learning Machines group, which will be shared between the autonomous matter and information in matter research themes at AMOLF. Stern’s research efforts will 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.
A theoretical physicist by training, Stern did his Ph.D. at The University of Chicago, in the group of Prof. Arvind Murugan. There he investigated mechanical systems like spring networks and self-folding origami as models for novel computation and learning. He is currently a postdoctoral fellow at The University of Pennsylvania, studying various aspects of physical learning algorithms and their implementations as learning machines.
