iGEM TIES (Teams IntEraction Study)
In this project we map the social interaction networks of scientific teams participating to the iGEM scientific competition. We collect high resolution team interaction data from digital traces, collaboration monitoring, and surveys to study the networks patterns underlying team performance and learning.
COVID19 Symptoms Twitter Analysis
We use a citizen-science approach to help analyse how local tweets about symptoms can predict hospital emergencies during a pandemic.
We reconstruct learner interaction network from phone call data to model the contagion process underlying the diffusion of knowledge in collaborative learning.
Analysis of Open Source Communities in GitHub
This project aims to quantify the organizational principles underlying large-scale self-organized open source communities.
The Rise and Fall of Scientific Fields
We use large datasets of scientific publications to understand the universal patterns underlying the growth and decline of scientific fields and describe the research trajectories of researchers in the knowledge space.
The biological networks driving ageing
We apply network science approaches to understand and model the dynamics of gene networks driving ageing in Drosophila and Humans. In particular, the project focuses on describing ageing as a propagation of network failures in the multi-layer interactome. The project is supported by a French national ANR JCJC funding.
Quantifying the organizational patterns of Citizen Science projects
In this EU H2020 project, we use digital traces to understand what makes citizen science projects succesful and how citizen scientists can provide reliable data for tracking the progress towards the UN Sustainable Development Goals and how grassroots innovation can help achieve such progress.
Designing recommender systems to enhance collective intelligence
In this project funded by a NESTA Collective Intelligence grant, we develop a network-based recommender system for the open science social platform Just One Giant Lab to match contributors to needs, and explore its impact on community self-organization.