|Talks|

The Impact of Higher Order Descriptions On Structural Analysis and Dynamical Processes

Visiting speaker
Past Talk
Giovanni Petri
Research Leader, ISI Foundation, Turin
Nov 5, 2019
10:00 am
Nov 5, 2019
10:00 am
In-person
4 Thomas More St
London E1W 1YW, UK
The Roux Institute
Room
100 Fore Street
Portland, ME 04101
Network Science Institute
2nd floor
Network Science Institute
11th floor
177 Huntington Ave
Boston, MA 02115
Network Science Institute
2nd floor
Room
58 St Katharine's Way
London E1W 1LP, UK

Talk recording

Topology, one of the oldest branches of mathematics, captures the concept of shape for spaces of arbitrary type and dimension. This allows to adopt some of its concepts to characterize and compare how complex systems evolve and restructure themselves. In the talk, I will introduce the most common topological techniques, persistent homology and Mapper, to illustrate what novel insights these new descriptive paradigms yield. In particular, I will focus on the impact of topological observables in the analysis of how the brain works at the functional, structural and genetic level, across a range of physiological and pathological conditions. I will then discuss recent advances in our understanding of the effects of higher order interactions on the evolution of dynamical processes, such as contagion and synchronization. Finally, I will discuss the challenges of inferring such higher order interactions in cases where they are not explicit, e.g. starting from timeseries data.

About the speaker
Giovanni Petri is a theoretical physicist that shortly after graduating decided that complex systems -- in the broadest sense -- were more intriguing than cosmology. He fell in love with the idea of high-order interactions, of emergent properties, etc. After obtaining a PhD on complex networks from Imperial College London, he started focusing on theoretical approaches at the interface of complex systems and algebraic topology. He is currently a Research Leader at ISI Foundation, where his research spans the analysis of neuroimaging data with topological techniques, the formalization of cognitive control models with tools of statistical mechanics and network theory, and the study of the predictability of socio-technical systems.
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Nov 05, 2019