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.