I am a graduate student at Stanford University in the Institute for Computational and Mathematical Engineering (ICME), formerly in the Applied Mathematics department at Ecole polytechnique, Paris. Prior to entering Ecole polytechnique, I was a Mathematics/CS preparatory class (Classe preparatoire) student at Lycee Sainte-Genevieve in Versailles.

My primary research interest is artificial intelligence. I am especially interested in building systems that can learn tasks from scratch (reinforcement learning) and/or use accumulated knowledge to efficiently learn new tasks (meta-learning). I am currently a research assistant in the Stanford Artificial Intelligence Lab, working with Prof. Emma Brunskill at the intersection of on- and off-policy reinforcement learning methods.

I am also highly interested in the statistical aspects of financial markets. At Ecole polytechnique, I worked with Prof. Jean-Philippe Bouchaud on some applications of control theory to trading. In 2018, I spent 6 months at Tower Research Capital in New York, where I worked on some applications of nonlinear machine learning techniques to high-frequency trading. This year (2019), I spent 3 months at Squarepoint Capital in Singapore, where I worked on several predictive signals on Asian equity markets.

I really enjoy teaching. I was a teaching assistant in Mathematics at Lycee Sainte-Genevieve in the academic year 2016-2017, conducting weekly oral examinations for undergraduates (linear algebra, real analysis, probability and group theory among other things). More recently, I have been a teaching assistant at Stanford for CS221 (AI: Principles and Techniques), in Fall 2018 and Spring 2019.

In my free time, I play a lot of music (acoustic and electric guitar). I also enjoy traveling and solving interesting puzzles.

Publications and preprints

Selected research projects

  • Image completion with neural processes (at Stanford, see details here).
  • Deep learning under massive label noise (at Tower Research).
  • Stochastic trust-region optimization algorithms, applications to traffic models (in collaboration with Aimsun).
  • Fair share problems (under the supervision of Prof. De Seguins-Pazzis).
  • An essay on the plactic monoid (RSK correspondence and the Erdos-Szekeres theorem).


benpetit [at] stanford [dot] edu