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François Durand

I was a student at the École Normale Supérieure, rue d'Ulm from 2000 to 2005. My formation was in Physics, Computer Science and Political Science. From 2003 to 2010, I worked in the humanitarian field as a trainer, financial coordinator and manager. From 2011 to 2015, I worked at LINCS, a joint lab between academics and industrials, as a research engineer in the GANG research team. In 2015-2017, I worked as a postdoctorate associate in a joint project involving the LAMSADE of Université Paris Dauphine and the CREM team of Université Caen - Basse Normandie. Since 2018, I have been working in the Gandalf team of Nokia Bell Labs France and back in the LINCS.

In my doctorate and posdoctorate works, I worked mostly on voting systems and their manipulability (tactical voting), using computer simulations and tools from game theory. For an overview, watch my PhD defense. I developped SVVAMP, Simulator of Various Voting Algorithms in Manipulating Populations, a Python package dedicated to the study of voting systems and their manipulability : These days I am more active on Whalrus (, a Python package dedicated to the use of various voting systems for practical applications.

Since 2018, I have embraced an additional axis of research: the application of deep neural networks to problems where communication and collaboration are the central issues.

Fabien Mathieu    41152   

Conference papers1 document

  • François Durand, Fabien Mathieu, Ludovic Noirie. Can a Condorcet Rule Have a Low Coalitional Manipulability?. European Conference on Artificial Intelligence (ECAI), Aug 2016, Den Haag, Netherlands. pp.707-715. ⟨hal-01369877⟩