Indiana University Indiana University IU

Event: MultiNet Webinar Series: Raissa M. D'Souza

Coevolution, ranking and optimal interventions in multiplex networks

Tuesday, Dec 8th 2020 at 11:00 a.m.

Event registration can be found here.

Title: Coevolution, ranking and optimal interventions in multiplex networks

Abstract: A collection of interdependent networks are at the core of modern society, from electric power grids, to the internet, to social and biological networks. Although there are many different forms of interdependence, one important paradigm is that of multiplex networks, where the same set of nodes can simultaneously have many different types of interactions. For instance, in a social network there can be both affiliative and agonistic interactions between the same individuals. Here we will focus on how to quantify the coevolution among the different types of interactions in multiplex networks, how to successfully develop ranking algorithms when the different types of interactions in a multiplex network are of radically different types, and methods for control interventions that consider trade-offs between the different types of interactions and also consider when the interaction types operate on different timescales. The work presented is inspired by and applied to critical infrastructure systems and macaque monkey societies.

Biography: Raissa M. D'Souza is a Professor of Computer Science and Mechanical Engineering at the University of California, Davis as well as an External Professor and member of the Science Board at the Santa Fe Institute. D'Souza uses the tools of statistical physics and applied mathematics to develop mathematical models capturing the interplay between the structure and function of networks, including dynamical processes unfolding on networks. Her focus is on the abrupt onset of large-scale connectivity in networks, network synchronization behaviors and models of cascading failure. The general principles derived provide insights into the behaviors of real-world networks such as infrastructure networks and social networks, and opportunities to identify small interventions to control the self-organizing, collective behaviors displayed in these systems. She collaborates broadly with faculty within the college and in physics, statistics, political science and the Primate Center.