Vincenzo (KatolaZ) Nicosia

Research Assistant

Research Assistant

Research interests

Since I was a child, I have had a genuine curiosity about anything
that exhibits patterns, regularities, self-organisation,
non-trivial interconnections and an overall unexpected
structure. This interest is probably the reason that led me to
start an academic career, driving my research towards the study of
complex systems. In particular, my current research interests
include:
In the past I have also been interested in the design of

**socially-inspired peer-to-peer networks**and in the design of control systems for**autonomous mobile robots**.
Structure of complex networks

A large number of experimental evidences have confirmed that many
real systems are can be represented as sets of elementary units
interacting through non-trivial networks of relationships. In the
last fifteen years the theory of complex networks has provided a
comprehensive framework to model and study these systems. The
systematic analysis of the structural properties of a complex
network can reveal important information about the overall
organisation of a system and about the role and function of each of
its elementary units. One of my major contributions in this field is
the extension of the **modularity**function for graphs with**overlapping communities**. I have worked on the**controllability of centrality**in complex networks, on the analysis of**functional human brain networks**, on the problem of defining**three-body correlations**and on the characterisation of the**evolution of road networks**. I am also interested in the analysis of the**evolution of neural networks**and in the characterisation of**symmetries in complex networks**.
Processes on complex topologies

The diffusion of a rumour on Facebook, the spread of a disease in a
country and of a virus in a corporate computer network, the
anomalous synchronisation of large areas of the brain observed
during an epileptic seizure, the formation of consensus and the
evolution of trends and tendencies on Twitter are all examples of
processes which evolve over a complex network. I have worked on the
characterisation of different processes occurring on complex
topologies, including **biased random walks**,**evolution of competing species**,**synchronisation**of mobile agents,**spreading of diseases**and diffusion of information. In particular, I am interested in the characterisation of**first passage times**for different classes of independent random walks on networks and in quantifying the impact of network structure on the evolution of**interacting random walks**. Time-varying graphs

Real networked systems, e.g. online social networks, contact
networks, functional networks of areas in the human brain, are
inherently dynamic, since the relationships among the nodes are not
persistent and usually fluctuate over time. However, up until
recently the studies on complex networks have been entirely based on
static graphs, where the connections among the nodes are given once
and for all. In the last few years, the concept of **time-varying graph**has been proposed as a model to incorporate time in the description of complex networks. I have worked on the**extension of centrality metrics**(including closeness and betweenness) and on the definition of**connectedness and connected components**for time-varying graphs, and I am currently working on the problem of defining and detecting**temporal communities**. I am also interested in the development of**models of temporal graphs**, and on the study of dynamical**processes on time-varying graphs**, including disease spreading, synchronisation and cooperative games.