Research interests

I am currently a Postdoctoral Fellow at the University of Missouri. I recently completed by PhD in computational sociology at the Interdisciplinary Centre for Science and Technology Studies in Wuppertal. I have a training in fundamental physics (École Normale Supérieure de Cachan and Université Pierre et Marie Curie) and in history and philosophy of science (Université Paris-Cité).

My research aims to understand how collectives generate, leverage, transmit, and sustain complex knowledge. In particular, I am interested in how individuals navigate social dilemmas in collective cognition, and in the resilience of cumulative learning.

I address these questions using computational models, empirical analyses of observational data, and since recently, online experiments. Most of my works appeal to Bayesian methods.

My PhD focused on social dilemmas in science, with an emphasis on high-energy physics, which is characterized by a strong division of labor. I showed that several major developments in this field may be understood as solutions to tradeoffs and dilemmas arising more generally in contexts of collective cognition. This work involved an interdiscplinary effort spanning across philosophy of science, social epistemology, cognitive science, and cultural evolution.

Parallel to my PhD, I worked at the ENS as part of the Language Acquisition Across Cultures team led by Alejandrina Cristia. This team studies Language Acquisition by collecting and analyzing long-form recordings capturing the speech production and environment of children.

In a previous life, I have also been a journalist and the publication manager for the french online media Le Média.

Energy transition

I have also started working on various pet projects about electric power systems and the energy transition. I have started designing a device for minimising the carbon footprint of the charge of electric batteries by optimising their schedule. My progress is documented here. For this project I use various components including an Arduino, combined with some modelling of the power system in order to forecast the optimal charge program for reducing carbon emissions.

For another project, my goal is to model electricity production and consumption in order to assess the resiliency of different scenarios, using various optimization and statistical modelling techniques. The project can be found on my GitHub.