Graphs and more Complex structures for Learning and Reasoning (GCLR) workshop was held at AAAI 2021. For more details about the workshop, please visit website: https://sites.google.com/view/gclr2021/.
Speaker's Bio: Prof. Manlio De Domenico is the Head of the Complex Multilayer Networks (CoMuNe) Research Unit at the Center for Information Technology of Fondazione Bruno Kessler, where he also co-coordinates the Computational Human Behavior (CHuB) FBK's Flagship Project. His research interests include structure, dynamics, emergence, and diffusion in complex networks. He is very actively working on the area of multilayer networks.
Title of the talk: Multilayer modeling of complex systems: from cells to societies
Abstract: Complex systems are characterized by constituents -- from neurons in the brain to individuals in a social network -- which exhibit special structural organization and nonlinear dynamics. As a consequence, a complex system can not be understood by studying its units separately because their interactions lead to unexpected emerging phenomena, from collective behavior to phase transitions.
In the last decade, we have discovered that a new level of complexity characterizes a variety of natural and artificial systems, where units interact, simultaneously, in distinct ways. For instance, this is the case of multimodal transportation systems (e.g., metro, bus and train networks) or of social networks, whose interactions might be of different type (e.g. trust, trade, virtual, etc.).
The unprecedented newfound wealth of data allows to categorize system's interdependency by defining distinct "layers", each one encoding a different network representation of the system. The result is a multilayer network model.
In this talk we will discuss the most salient features of multilayer systems and how to determine their robustness, node versatility and mesoscale organization, with special attention to applications to empirical biological, socio-ecological and socio-technical networks. We will also discuss recent applications to systems medicine and infodemiology of COVID-19.