Our research focuses on the structure, dynamics and physics of complex networks emerging from the intricate interconnectedness of the constituents of large systems. Complex networks naturally emerge in financial, economic, social, neural and biological systems. We combine a theoretical approach, largely based on statistical physics, information theory, discrete mathematics and complexity science, with a data science approach informed by the empirical properties of real-world networks. Given the strong interdisciplinarity of our research, we regularly collaborate with experts in other fields, especially mathematics, computer science, economics, finance and neuroscience.
As part of our teaching activity at IMT School, we provide advanced PhD courses on Network Theory, Complex Systems, and several applications. The topics covered include the theory of modern statistical physics, a complexity-theory approach to economic and financial systems, and the analysis of time-correlated activity in different areas of the brain.
Our Journal Club is NEDO (NEtwork Discussions On..).
Our page collecting codes and algorithms emanating from our research is MEH (Maximum Entropy Hub).
Welcome to this web site and contact us if you are interested in our activities.