Description:

Abstract: This talk focuses on understanding, predicting, and ultimately controlling real-world complex systems in an ever-changing world facing the global challenges of climate change, weather extremes, and other natural and human-induced disasters. I will present our recent works in the field of network science and complex systems about the dimension reduction approach for network resilience. (i) I will briefly introduce our dimension reduction approach to identify the natural control and state parameters of a multi-dimensional complex system, helping us derive an effective one-dimensional dynamic that accurately predicts the system's resilience.  (ii) We develop a rescaling factor for recovery rates that places various systems with entirely different dynamical parameters, network structure, and state perturbations on the same scale. More importantly, it compares distances to tipping points across multiple systems based on the limited data of abundance and topology.  (iii) Finally, we show how to restore failed systems through microscopic interventions and system noises.

Speaker: Jianxi Gao, Assistant Professor of Computer Science, Rensselaer Polytechnic Institute

Host: Professor Adilson Motter