I am currently a postdoctoral fellow in Network Science and Data Science.
My background is in Computer Science and during my PhD, I focused on graph theory and its application to social network analysis. In particular, I studied the structure of bipartite networks and developed algorithms to exhibit their community structure. Using these developed tools I studied how individuals organize into communities on platforms such as Wikipedia, Meetup or Yelp.
One of my goal is to develop applications that will collect various type of data coming from students participating at the iGEM competition. For instance, I develop smartphone applications that can capture physical and social interactions between team members by using bluetooth as a sensor.
Raphael hasn't filled hers/his bio yet.
iGEM TIES (Team IntEraction Study): mapping social interaction networks of iGEM scientific teams
In this project, we study the collaboration patterns of iGEM teams underlying their performance and learning using data-driven social network analyses
Big data for collective emotion analysis
We leverage large scale data from Youtube and Twitter to analyse the dynamics of collective emotions
A quantitative study of interdisciplinarity and team performance in the iGEM competition
Quantifying how background and skills diversity affect team performance in iGEM teams