Alessandro Vespignani is an Italian American physicist whose research sits at the intersection of computational modeling, data science, and complex systems, with a focus on contagion phenomena, collective behavior, and epidemic preparedness. He trained in theoretical physics in Rome, held postdoctoral posts at Yale and Leiden, and later worked at the International Center for Theoretical Physics and Indiana University before joining Northeastern University, where he is the Sternberg Family Distinguished University Professor of Physics, Computer Sciences, and Health Sciences. He directs Northeastern’s Network Science Institute and MOBS Laboratory, serves as President of the ISI Foundation in Turin, Italy, and helps lead EpiStorm, a CDC initiative that models and forecasts epidemics.

In this wide-ranging InterDialogue, Vespignani traces network science’s shift from foundational theory toward urgent, data-driven application, and discusses the community, funding, and technological forces behind that growth. He makes the case for science as a collective, interdisciplinary effort—increasingly recognized by policymakers and the public—and walks through his own path from theoretical physics in Rome, through Yale, Leiden, and the ICTP, to the landmark papers and books that helped define the fields of complex networks and computational epidemiology.

The conversation turns to Vespignani’s public health work over the last two decades—including CDC forecasting through FluSight and EpiStorm, and his team’s recent role in the Ebola response in the Democratic Republic of the Congo—and to what differentiates outbreaks like COVID-19, influenza, and Zika. We close on the erosion of public trust in science, the broad work being done at institutions he leads at Northeastern and at ISI Foundation, and how artificial intelligence is reshaping the scientific enterprise.

Timestamps

0:00 – Introduction

2:20 – The growing urgency of network science

5:58 – From toy models to real-world data

8:56 – Data, community, and funding as growth drivers

13:19 – Science as a collective, interdisciplinary effort

19:53 – Interdisciplinarity’s reach into policy and public awareness

22:16 – Bridging data science and the social sciences

27:29 – Vespignani’s path from physics to network science

37:44 – The scale-free networks paper and the internet book

44:54 – Fifteen years of public health modeling at MOBS

50:41 – Connecting modelers with doctors on the front lines

53:24 – Why every disease outbreak is different

57:39 – The interdisciplinary team behind epidemic forecasting

58:59 – Responding to the Ebola outbreak in Africa

1:04:14 – Fighting misinformation and rebuilding trust in science

1:08:32 – Building the Network Science Institute and ISI Foundation

1:14:36 – AI’s growing impact on network science