photo de profil d'un membre


Hugo SONNERY (CS promotion 2021)

19 ans

Situation professionnelle

Épanoui(e) professionnellement

Formations complémentaires

Développement Web

3W Academy - HTML, CSS, JS, jQuery, PHP, SQL

2014 à 2014

Formation en présentiel au métier de développeur / intégrateur Web (Front End & Back End) par cours et projets.

M2 MVA (Machine Learning)

École Normale Supérieure Paris-Saclay - Applied Mathematics & Machine Learning

2020 à 2021

First semester :
- Reinforcement Learning (Alessandro LAZARIC)
- Probabilistic Graphical Models (Francis BACH)
Second semester :
- Multi-scale models and RNNs (Stéphane MALLAT)
- Graphs in Machine Learning (Michal VALKO)
- Theoretical foundations of Deep Learning (Nicolas THOME)
- Kernel Methods for Machine Learning (Jean-Philippe VERT)
- Bayesian Machine Learning (Rémi BARDENET)
- Algorithms for Speech and NLP (Emmanuel DUPOUX)
Optional Research project : Deep Reinforcement Learning for Polyphonic Music Performances Generation

M2 Cursus Ingénieur

CentraleSupélec - Machine Learning & Data Science

2020 à 2021

Elective courses (Research & Data Science track) :
- Deep Learning
- Large Scale Distributed Computing and Optimization
- Advanced Multivariate Data Analysis
- Random Matrix Theory and Applications to Machine Learning
- Machine Learning in Network Science
- Advanced Machine Learning
- Advanced Statistics
- Convex Optimization
- Stochastic processes and calculus
- Temporal sequences
Research project in Graph Knowledge Extraction from Scientific Papers.
Class representative in most courses.

M1 Erasmus Exchange

Trinity College, University of Cambridge - Mathematics for Machine Learning, Neuroscience & Biology

2019 à 2020

- Mathematical methods & Scientific computing
- Bayesian Inference
- Statistical signal processing
- Information theory and coding
- Introduction to molecular bioengineering / Introduction to Neuroscience
- Medical imaging and 3D computer graphics / Biomaterials
- Organisational Behaviour / Business Economics
- Design of Baseband-OFDM / DMT audio modulation system (end-of-study project)

Bachelor of Engineering

CentraleSupélec - Computer Science and Engineering

2018 à 2019

- Statistics and machine learning
- Convergence, integration, probability and partial differential equations
- Information systems and programming
- Algorithmics and complexity
- Advanced computer science course (optional class)
- Black swans detection in particle physics / data analysis in cosmology
- Signal processing theory
- Quantum and statistical physics
- Antennas and resilient communication systems
- Corporate accounting and finance / business management
Exploration classes :
- Electronic systems / Electrical energy
- Continuum mechanics
- FM stereophonic radio (optional project)
- English (advanced level) / Spanish (confirmed level)
Class representative in most courses.

Bachelor in Fundamental Physics (Double degree)

Université Paris-Sud

2018 à 2019

Elective classes :
- Quantum mechanics
- Electrodynamics
- Analytical mechanics
- Wave optics
- Statistical physics
- Special relativity.
Optional class : History of Science


Lycée du Parc

2016 à 2018

First year in MPSI 1, second year in MP *.
Eligible to admission at Polytechnique, ENS Rennes, Mines Paris, CentraleSupélec.
Admitted at ENS Rennes, ESPCI and Centrale Paris.
TIPE project : Monte-Carlo methods for efficient multidimensional integration.
In Lyon, France.


Ciné-Club CentraleSupélec


Parcours officiels

CentraleSupélec – Ingénieur – 2021


Anglais - Courant

Espagnol - Courant

Français - Langue maternelle

Latin - Technique