The fundamental research conducted at the Lagrange Laboratory on Complex Systems is divided into five lines as follows:

Computational and Digital Epidemiology
The activity of Computational and Digital Epidemiology domain research focuses on the development of mathematical and computational tools to predict the spread of infectious diseases. Within this domain, in 2008 we established a Web-based platform for participatory influenza surveillance in Italy called Influweb. The participatory surveillance paradigm has been extended during the following years to other European countries to build what is now known as Influenzanet, a network of Web platforms for flu surveillance adopted by many public health institutions all over Europe. The group also collaborates with Northeastern University (Boston, MA) and has intervened as a crisis unit during the most recent public health emergencies related to emerging infectious diseases, such as the 2009 H1N1 pandemic, the 2015 West African Ebola outbreak and the 2016 Zika virus epidemic.
Computational Social Sciences
The activity of Computational Social Science domain research aims at investigating social phenomena through the medium of computing and related advanced information processing technologies, leveraging the capacity to collect and analyze data with an unprecedented breadth, depth and scale.
Data for Good
The activity of the Data for Good domain research is mainly focused on bringing the data science expertise of ISI researchers to the service of non-profit organizations that are working in the field of social innovation, philanthropy, international development and humanitarian action. Within the Data for Good domain, the ISI Foundation has established research partnerships with various organizations of the United Nations such as UNICEF, Data2X and the UN Global Pulse. Such collaborations take form of Data Collaboratives, as recently defined by the GovLab of NYU.
Mathematics & Foundations of Complex Systems Science
The Mathematics & Foundation of Complex Systems domain research aims to provide rigorous theoretical research on complex systems and using new topological and algebraic methods to extract information from data.
Particular areas of interest and application include neurosciences, the brain and intelligence models.
Data Science
The activity of the Data Science domain research comprises those research lines that regard digital traces of human behaviour as first-order objects for scientific investigation. The main goal of the research group is to extend the traditional toolbox of complex systems research with data mining and machine learning techniques and with the use of scalable computational infrastructures that can deal with large-scale records of activity from modern techno-social systems.