My Resume


schoolENS Paris

ENS Diploma in Computer Science

The Ecole Normale Supérieure is a prestigious institution of higher education providing specialized training to students who will become researchers in their fields.

schoolParis Dauphine

Master 2 Artificial Intelligence, Systems and Data (IASD)

The IASD Master program aims at training students with a strong theoretical knowledge and a practical experience in AI and Data Science. Its goal is to provide students with a solid and general understanding of modern artificial intelligence, so they can build robust and reliable AI systems. My coursework includes:

  • Advanced databases (non-classical DBMSs)
  • Machine learning fundamentals
  • Optimization for machine learning
  • Data science project
  • Deep learning
  • Knowledge representation, planning, and reasoning
  • Advanced machine learning
  • Computational social choice
  • Data wrangling, data quality
  • Deep learning for image analysis
  • Incremental learning and game theory
  • Knowledge graphs, description logics, reasoning on data
  • Natural language processing

The various projects done during this Master program can be found on this page.

schoolENS Paris
gradeHighest honours

Master 1 in Computer Science

I followed computer science courses during the first semester for this M1. I also followed some neurosciences courses. My coursework includes:

  • Introduction to statistical learning
  • Artificial vision
  • Network algorithms
  • Prediction of robotic movement
  • Information systems security
  • Introduction to linguistic (neurosciences course)
  • descriptive and functional neuroanatomy (neurosciences course)

The various projects done during this program can be found on this page.

schoolENS Paris
gradeHighest honours

Bachelor degree (L3) in Computer Science

My coursework includes:

  • Algorithmic and programming
  • Programming languages ​​and compilation
  • Digital systems: from algorithm to circuit
  • Information theory and coding
  • Introduction to databases
  • Operating systems
  • Random structures and algorithms
  • Formal languages, computability and complexity
  • Introduction to cryptology
  • Introduction to research in computer science
  • Introduction to decision science (neurosciences course)
  • Introduction to computational neurosciences (neurosciences course)

The various projects done during this program can be found on this page.

schoolCPGE Lazaristes

Classe Préparatoires in Mathematics and Physics

  • Admitted to Ecole Polytechnique
  • Admitted to Ecole Normale Supérieure Paris (4th)


access_time6 months

Multi-Winner Voting Rules

Stage in progress...
Advisors: François Durand and Fabien Mathieu.

access_time5 months
apartmentENS Paris

A Knowledge Base of Mathematical Results

We implemented an algorithm to automatically extract mathematical results and references to them from scholarly documents and used it on the whole ArXiv database. See the details on this page.
Advisor: Pr. Pierre Senellart.

access_time5 months
location_onNew York

Algorithms and Systems for Computational Social Choice: Incorporating Context into Preference Aggregation

I implemented and optimized algorithms to solve necessary and possible winner problems in the context of partial preferences. I also ran an experiment to collect partial preferences data and proposed a new method to generate artificial data for partial preferences. See the dedicated page of this project.
Advisor: Pr. Julia Stoyanovich.

access_time2 months

Make understandable the access controlsof social networks.

I built a formal model for access controls on social networks and solve complexity problems on this model. I also created a tool/compiler which enable to do huge queries on the Facebook database. See the dedicated page of this tool.
Advisors: Pierre Bourhis, Romain Rouvoy, Walter Rudametkin.



  • Algorithmic Techniques for Necessary and Possible Winners, May 2020, Vishal Chakraborty, Theo Delemazure, Benny Kimelfeld, Phokion G. Kolaitis, Kunal Relia, Julia Stoyanovich
  • Skills


  • French: Mother tongue
  • English: Good command
  • Spanish: Basic Knowledge
  • Programming and Design

    Programming and Databases:

    • Python
    • Java
    • C (Basic Knowledge)
    • OCaml
    • PHP
    • Javascript
    • Shell
    • SQL
    • SPARQL
    • Neo4j


    • LaTeX
    • HTML
    • CSS
    • React Native

    Python libraries:

    • Pytorch
    • Keras
    • Pandas
    • etc.