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Disordered Systems

The Disordered Systems group at King's is at the forefront of research in statistical mechanics of disordered and complex systems. The research of the group concentrates on the development of new methods to tackle both fundamental issues, for example in non-equilibrium systems, and a broad range of applications to complex systems of many interacting units. The latter include mathematical systems biology and quantitative medicine (protein, metabolic and immune networks & network ensembles) as well as links with statistics and informatics in the area of Bayesian statistical inference and machine learning. The group also has a strong profile in soft condensed matter physics (rheology, polydispersity), glasses and driven non-equilibrium systems. Recent work has led to the development of new models to describe natural and social phenomena, such as systemic risk and catastrophic breakdown in complex systems, with applications to finance and the prediction of power outages. Random matrix theory has become an increasingly important area, studied using extensions of methods for sparse networks