About

👋 Welcome on my website.

I wanted to build a space to share my notes, my ideas, my projects, and I hope you’ll find it useful or interesting.

I am interested in a lot of research domains, including:

Signal Processing and Machine Learning (especially for audio);
Combinatorial Optimization and Graph Theory (especially the now popular field of Graph Machine Learning);
Links between Cognitive Science and Machine Learning and Biology-inspired Computer Science (Evolutionary ML, Bioinformatics);
Ethics and Technology;
Natural Language Processing;
Deep Learning Theory;
Federated Learning;
… I am curious and pick interest in many projects.

Facebook AI Research (Jul. - Nov. 2020): Noise-robust ASR.
ENS Paris (Apr. - Aug. 2019): Adult/Child directed speech & Voice Activity Detection for Diarization.
CentraleSupélec (Oct. 2018 - Mar. 2019): FPT algorithm for vertex/edge min-cut enumeration.
Snips (now Sonos) (Jun. - Aug. 2018): Embedded Voice assistant applications.

with highest honors 🏅

Class	Lecturer	Mark
Convex optimization and applications in machine learning	A. d'Aspremont	19.4 / 20
Introduction to digital imaging	J. Delon	15.0 / 20
Image denoising : the human machine competition	J.-M. Morel G. Facciolo	17.6 / 20
Reinforcement Learning	A. Lazaric	17.0 / 20
Graphs in Machine Learning	M. Valko	18.27 / 20
Deep Learning		19.0 / 20
Internship	G. Synnaeve	16.5 / 20
Multi-scale models and convolutional neural networks	S. Mallat	16.0 / 20
Audio Signal Analysis, Indexing and Transformations	G. Richard	16.0 / 20
Introduction to Medical Image Analysis		14.5 / 20
Kernel methods for machine learning	J.-P. Vert	11.0 / 20
Deep learning in practice		12.7 / 20
Algorithms for speech and natural language processing	E. Dupoux B. Sagot	13.1 / 20
Average		17.02 / 20

CentraleSupélec: MSc. in Engineering & Major in Computer Science (diplôme d’ingénieur).
with highest honors 🏅
(in parallel) Université Paris-Saclay: MSc. in Computer Science and Machine Learning.
with highest honors 🏅