Research

The research on multi-agent networked control has drawn significant inspiration from interaction-rules observed in real life such as fish schools, locust swarms, and bird flocks, social network. The study of these complex networks, i.e. networks whose structure is irregular, complex and dynamically evolving in time has the main focus of moving from the analysis of small networks to that of systems with thousands or millions of nodes, and with a renewed attention to the properties of networks of dynamical units. Scientists have to cope with structural issues, such as characterizing the topology of a complex wiring architecture, revealing the unifying principles that are at the basis of real networks, and developing models to mimic the growth of a network and reproduce its structural properties. In the recent years, the Dynamical System Lab at NYU POLY have drawn significant results on the subject. Under the supervision of Professor Maurizio Porfiri, I expect to improve some of the methodology developed earlier looking for more innovative and relevant  approach to model and synchronize complex and chaotic network system. This will be achieved by using advanced mathematical modeling of stochastic switching network, numerical simulations to test and validate numerically these models, some data measurement to match the theoretical aspect of the research with the reality and the development of practical tools for Network synchronization that include but are not limited to software, sensors, feedback control.

Fig: A complex graph network structure