Nicolas Flammarion awarded the Gaspard Monge Program Thesis Prize

Can you tell us about your career?

After a CPGE (Higher School Preparatory Class) in science, I went to the Ecole Normale Supérieure in Lyon to study mathematics. After deciding that I wanted to specialise in the field of probabilities, I discovered the field of statistical learning and did the Master of Mathematics / Vision / Learning (MVA) at ENS Cachan. I attended the course of Francis Bach, for which I joined the Inria team to pursue my thesis there. I am now a post-doctorate fellow at the University of California, Berkeley, hosted by Michael Jordan. 

You received the Gaspard Monge Program award, can you tell us about this?

This is an award founded by the Jacques Hadamard Mathematical Foundation which each year aims at rewarding doctoral theses that “make significant contributions in the field of optimisation and operational research”. 

What research project did you present?

I presented my thesis. This mainly focused on the design and analysis of optimisation methods applied to machine-learning problems, in particular on first order algorithms for convex stochastic approximation problems. 

What does this distinction mean to you?

Paradoxically, research is an area in which we rarely receive feedback, except when an article is accepted. It is therefore both stimulating and rewarding to know that well-respected researchers have appreciated our work. It is also obviously an amazing opportunity for me to present my research during the day(s) [sic]