Pierre Bras is a second-year PhD student at LPSM Sorbonne Université under the direction of Gilles Pagès. His research focuses on numerical methods for probability and statistics with applications to Machine Learning and Finance.

Interests

- Numerical Probability
- Stochastic Optimization
- Machine Learning
- Monte Carlo methods
- Stochastic Calculus
- Mathematical Finance
- Stochastic control

Education

PhD in Applied Mathematics, 2020-2023

Sorbonne Université, LPSM

Master 2 Probability and Random Models, option Applied Probability, 2019

Sorbonne Université, LPSM

Diploma of Ecole Normale Supérieure in Mathematics and Applications, 2016-2020

Ecole Normale Supérieure de la rue d'Ulm

Total variation convergence of the Euler-Maruyama scheme in small time with unbounded drift.
In *arXiv e-prints*.

(2021).
Convergence of Langevin-Simulated Annealing algorithms with multiplicative noise .
In *arXiv e-prints*.

(2021).
Convergence of Langevin-Simulated Annealing algorithms with multiplicative noise II: Total Variation.
In *arXiv e-prints*.

(2021).
Simulation of Reflected Brownian motion on two dimensional wedges.
In *arXiv e-prints*.

(2021).
Convergence rates of Gibbs measures with degenerate minimum.
Accepted for publication in *Bernoulli*.

(2021).
- pierre.bras@sorbonne-universite.fr
- 4 Place Jussieu, Paris, 75005
- Couloir 16-26 Bureau 201