Student in Machine Learning.

Graduated from MVA, ENS Paris Saclay

I am in theComputer Science Department of ENS de Lyon. I enjoy a rather formal and mathematical approach of computer science. I like to design algorithms, try new ideas in small implementations and think about social impact of science. So I have chosen my studies in according to this three aspects:

  • Mathematical rigor, because I need to understand how it works and theory provides a special kind of harmony
  • Computer science problems, as there are so many interesting challenges, especially in machine learning and distributed setting, and coding provide "experimentation" with just a computer
  • Philosophy of sciences, because techniques and science embodies implicit definitions of our world and thinking about them with another perspective, using known sociological and philosophical concept is a necessary complement.
I am currently in a double diploma to become also an Engineer of Mines Paristech, member of PSL. You can look a eye to my some work done during my studies. I was lucky to discover fascinating maths as a young student with volunteers of Animath, I now try to pass on this interest to other students, to give them the same opportunities than I had. I participated in events dedicated to girls, as I am convinced of their necessity to build a fairer world. More globally, I also enjoy teaching and share knowledge with others.

First paper published !

Privacy Amplification by Decentralization

My internship with Aurélien Bellet is now published, you can find it here. I present it at PPML and SpicyFL workshops at NeurIPS.

We introduce a novel relaxation of local differential privacy (LDP) that arises naturally in fully decentralized protocols, where participants exchange information by communicating along the edges of a network graph. This relaxation, called network DP, captures the fact that users have only a local view of the decentralized system.

Here is the paper.