Modeling and forecast of socio-technical systems in the data-science age


NICO Distinguished Speaker Series, 2:00pm, October 11th, James Allen Center

Prof. Alessandro Vespignani,  Northeastern University


In recent years the increasing availability of computer power and informatics tools has enabled the gathering of reliable data quantifying the complexity of socio-technical systems. Data-driven computational models have emerged as appropriate tools to tackle the study of contagion and diffusion processes as diverse as epidemic outbreaks, information spreading and Internet packet routing. These models aim at providing a rationale for understanding the emerging tipping points and nonlinear properties that often underpin the most interesting characteristics of socio-technical systems. Here I review some of the recent progress in modelling contagion and epidemic processes that integrates the complex features and heterogeneities of real-world systems.


Alessandro Vespignani is Sternberg Distinguished Professor at Northeastern University in Boston, where he leads the Laboratory for the Modeling of Biological and Socio-technical Systems. He is fellow of the American Physical Society, member of the Academy of Europe, and fellow of the Institute for Quantitative Social Sciences at Harvard University. He is also serving in the board/leadership of a variety of journals and the Institute for Scientific Interchange Foundation. He is  focusing his research activity in modeling diffusion phenomena in complex systems, including  data-driven computational approaches to infectious diseases spread.