Current Projects

COVID-19 Modeling and Forecasting

In response to the ongoing COVID-19 outbreak, we extended the Global Epidemic and Mobility model (GLEAM) to incorporate the effects of travel restrictions, non-pharmaceutical interventions, age-structured contact patterns, and vaccination campaigns to study, project, and forecast the evolution of the COVID-19 pandemic. Read more..

Deep Learning + Epidemic Modeling

We combine traditional epidemic modeling approaches with state-of-the-art machine learning and deep learning methods to improve forecasts, accelerate large-scale stochastic simulations, and reconstruct the early stages of an epidemic. Read more..

Multiscale Epidemic Modeling

We introduce a multiscale modeling approach to study the diffusion and impact of SARS-CoV-2 at both global and local scale combining epidemic models that work at different geographical resolutions. Read more..

GLEAM Project

The Global Epidemic and Mobility project, GLEAM, combines real-world data on populations and human mobility with elaborate stochastic models of disease transmission to deliver analytic and forecasting power to address the challenges faced in developing intervention strategies that minimize the impact of potentially devastating epidemics. Read more..


Past Projects

Mapping the physics research space

Scientific discoveries do not occur in vacuum but rather by connecting existing pieces of knowledge in new and creative ways. Mapping the relation and structure of scientific knowledge is therefore central to our understanding of the dynamics of scientific production. In this project we introduce a new approach to generate scientific knowledge maps based on a machine learning approach. Read more..


Analyzing political preferences and projecting the results of the 2016 Italian constitutional referendum using Twitter, network science, and natural language processing. Read more..