My main research interests lie in the interplay between Neural Networks and Bayesian statistics. I'm mainly interested in Generative model and the inherent implicit biases defined by Neural networks and how can we use them to solve several (Bayesian) problems, namely Inverse problems but also in Simulation-based Inference (or Likelihood-free inference). You can find a list of my publications on Google Scholar.

Click here for a detailed CV.

In a nutshell, I obtained my Ph.D. in April 2024 from Institut Polytechnique de Paris, France, working with E. Moulines and R. Dubois on levaraging Generative models for the Electrocardiogram (ECG). Prior to my Ph.D., I worked as a Machine Learning engineer at Volta Medical.

In september 2024 I joined the Geostatistiques team from Ecole des Mines (PSL University) as an Assistant professor (Tenure track position).

List of tutorial talks and links:

• Slides and Notebook of the talk "Introduction to Score Based Generative models" presented in the Hi! Paris reading group. (Link for notebook in the github)