Image of Alessandro Rizzo


Modeling and forecasting epidemics have had a century-long history within the scientific community, dating back from the early nineteen-hundreds. At that time, big cities began to flourish worldwide, constituting the most important fabric upon which epidemics can spread. Since the inception of the COVID-19 pandemic, however, epidemic predictions have abandoned the strict circle of scientists and have started to entice the general public, raising as much interest as weather forecast. The two activities have many aspects in common; however, forecasting epidemics is subject to additional sources of uncertainty: human heterogeneity and behavior, spatial distribution and, today more than ever, rapid travels. Still nowadays, the role of cities is key in shaping the course of an epidemic, whereby a localized spread can easily turn in a planetary threat. 

In this talk, I will revise basic concepts of epidemic modeling, starting from the forefather (and simplest) approach, which assumes that people perfectly mix all together like cocktail ingredients in a shaker, toward more and more complex modeling techniques designed to account for realistic features of humans, leveraging graph theory, statistical physics, data science and agent-based computations. I will also guide you through some milestones of our research results, obtained in collaboration with the Dynamical Systems Laboratory of NYU Tandon. We will deal with some methodological aspects and, most importantly, applications, including our efforts on Ebola in West Africa and on COVID-19 in New York State and in Italy.

Image of Alessandro Rizzo

Alessandro Rizzo, Associate Professor at Politecnico di Torino, Italy; Visiting Professor at the Institute of Invention, Innovation, and Entrepreneurship, NYU Tandon School of Engineering

Alessandro Rizzo is an Associate Professor at Politecnico di Torino, Italy, where he directs the Complex Systems Laboratory. He is also a Visiting Professor at the Institute of Invention, Innovation, and Entrepreneurship at the New York University Tandon School of Engineering. Dr. Rizzo conducts and supervises research on modeling, analysis and control of complex systems and networks, distributed estimation and control, bioinspired and distributed robotics, and nonlinear dynamics. He holds two international patents; he authored one book and more than 200 papers in peer-reviewed international journals and conference proceedings. He is a Senior Member of the IEEE and a Distinguished Lecturer of the IEEE Nuclear and Plasma Science Society and was the recipient of two Amazon Research Awards in Robotics, in 2019 and 2021.