Fernando Lucas Metz
(Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil)
Izaak Neri
(King's College London, UK)
Isaac Pérez Castillo
(Universidad Autonoma Metropolitana, Mexico City, Mexico)
Random matrix theory was initiated about 80 years ago as a new mathematical tool to study many-body systems, such as, heavy nuclei or atoms. Standard models of random matrix theory rely on independent and identically distributed matrix entries. Recent years, new random matrix models have been developed that incorporate features of real-world systems, such as, network architecture, modularity, and recurrent motifs. These network models appear in the study of complex systems, such as, financial markets, signalling networks, neural networks, or ecosystems. Potential topics of the workshop are the analysis of systemic risk in financial markets, the stability of ecosystems, or applications of random matrix theory in statistical inference, to name a few. The aim of the workshop is to bring together researchers working on random matrix theory and complex systems.
Stefano Allesina (US)
Ariel Amir (US)
Charles Bordenave (FR)
Jean-Philippe Bouchaud (FR)
Fabio Caccioli (UK)
Andrea De Martino (IT)
Carl Dettmann (UK)
Joshua Feinberg (IL)
Thomas Guhr (DE)
Boris Khoruzhenko (UK)
Reimer Kühn (UK)
Carlo Lucibello (IT)
Antoine Maillard (FR)
Satya Majumdar (FR)
Matteo Marsili (IT)
Rémi Monasson (FR)
David R. Nelson (US)
Maciej Nowak (PL)
Srdjan Ostojic (FR)
Federico Ricci-Tersenghi (IT)
Tim Rogers (UK)
Marc Timme (DE)