My research interests
Big Data Analytics The accessibility to large quantities of data combined with the great storage capabilities and cutting-edge computational tools makes possible to investigate complex systems, such as financial markets, in a new quantitative manner. I am developing tools to extract meaningful information from very large complex datasets.
Filtering I investigate new ways to filter
information from complex data by constructing networks of
dependency and causality relations that provide information
about the collective behavior of the system, the heterogeneous
distribution of response to external or internal changes and
interrelation between the parts.
and Muliscaling I investigate the complexity
of the evolution pattern of a variable in time extracting
scaling laws which can provide information on the stability of
the observed behavior and give insights on the future
Complexity I study how complexity can offer stability, robustness, adaptation and spontaneous organization to complex systems. Natural systems have long exploited complexity we are learning from the biological world how to integrate complexity in the design of new artificial systems.
I explore novel methods to generate and characterize complex
networks by means of their embedding on hyperbolic surfaces.
This method provides a new perspective to network theory and
opens no ways to use networks for the investigation of complex
systems and financial markets.