Disordered Systems

Our research activities concentrate on the analysis and development of mathematical theories and models for statics and dynamics of disordered (or complex) systems in physics, biology, financial markets, and computer science. Examples are (spin)-glasses; quantum spin chains; packing problems; fracture, folding and crumpling; mechanical behaviour and flow of amorphous materials; protein interaction networks; metabolic networks and processes and inference on complex networks more generally; random matrices; agent based models; systemic risk and financial contagion dynamics; Bayesian inference; and machine learning.

All these systems are usually characterized by microscopic stochastic dynamic elements with mutual interactions without global regularity but with a large degree of built-in competition and incompatibility, resulting in highly complex and non-ergodic types of dynamics.