Our research interests are both theoretical and applied in nature.
Mathematical modelling of complex networks via maximum-entropy ensembles of random graphs with prescribed properties;
statistical physics of systems for which the fundamental assumption of ensemble equivalence is broken by the presence of local constraints;
design of renormalisation schemes for the analysis of networks at multiple scales;
construction of null models of complex systems for statistical pattern detection;
introduction of methods for the detection of mesoscopic levels of organization in complex systems from empirical time series or other features;
refinement of traditional information-theoretic bounds on data compression for large data structures with heterogeneous properties.
Reconstruction of financial networks from partial information and reliable estimation of systemic risk from privacy-limited data;
detection of early-warning signals of upcoming instabilities in financial and banking systems;
multi-scale analysis and modelling of economic networks with nontrivial topology;
study of functional brain networks in healthy subjects and diseased patients;
analysis of social networks, (mis)information diffusion, polarization, opinion dynamics;
urban growth, metabolism, and sustainability.