Career Profile
Hi, I recently graduated with a PhD in Machine Learning, focusing on the use of evolutionary methods for the optimization of neural networks as intelligent agents. I specialize on learning methods that combine evolution, Reinforcement Learning and Quality-Diversity, and in my current postdoc at Imperial College London I focus on their application to adaptive and intelligent robotics. With a background in engineering combined with experience in consulting and teaching, I have built a wide range of skills to be comfortable at all stages of development: from research to implementation, from technical depth to high-level communication, from individual work to team collaboration.
Work Experiences
Postdoc at Imperial College London focusing on adaptive and intelligent robotics, while continuing research on evolutionary methods and Quality-Diversity.
Research on Evolution Strategies for policy search, covering deep RL, Quality-Diversity, Genetic Programming. Teaching: 150h in Python and Evolutionary Computation. Co-supervision of an intern leading to a CEC paper.
Visiting student at Antoine Cully’s Adaptative & Intelligent Robotics Lab (AIRL) at Imperial College Londo, focusing Evolutionary RL and mixes of ES with Quality-Diversity. This collaboration lead to 2 published articles and a postdoc.
Evolution of neural networks with genetic algorithms for to video games. Implementing NEAT, HyperNEAT in Julia. Ranked first in the GECCO 2020 competition on evolving a DOTA 2 bot.
Internship subject: uses of AI for cybersecurity intrusion detection & response, implementation of a PoC. Other missions: EBIOS risk analysis, impacts on cybersecurity of emerging technologies (i.e. quantum computing).
Leading high-stake international projects with long-term implications in an AI-focused startup.
Education
PhD in evolutionary machine learning, focusing on the optimization of neural networks with Evolution Strategies, their interactions with Deep Reinforcement Learning and Quality-Diversity.
Masters in general engineering, applied to aerospace problems. Specialized in Data Science (major) and Robotics (minor). GPA: 4.18. Research projects:
- Deep Learning to solve NP-hard problems
- Deep Reinforcement Learning for human-machine cooperation.
Additional MSc coupled with the Data Science specialization with classes on:
- Optimization,
- Advanced combinatorial optimization
- Stochastic and evolutionary methods
Publications
Peer reviewed:
Blog articles:
Grants & Awards
Grant to visit the AIRL lab at Imperial College London for 4 months. Combines grants awarded by ISAE-SUPAERO and the EDMITT doctoral school.
3-year PhD scholarship from Région Occitanie, covering tuition fees and a monthly stipend.
3-year PhD scholarship from ISAE-SUPAERO, to complete the Région Occitanie funding.
Best Paper Award at GECCO 2024 for the article “Quality with Just Enough Diversity in Evolutionary Policy Search”, in the combined tracks of Complex Systems and Learning for Evolutionary Computation.
First place at the GECCO 2020 competition on evolving a Dota 2 bot for 1v1 matches, with Lucas Hervier and Dennis Wilson.
Talks
GECCO 2024 (recorded) (Video)
Presenting our JEDi paper at GECCO 2024. The video was pre-recorded, and the live talk was presented by Dennis Wilson.
CEC 2024 (Yokoama, Japan) (Video)
Presenting our GDR paper at CEC 2024. The video was pre-recorded.
Théâtre Sorano (460 people) (Video)
Regional finals of the MT180 competition, where PhD students have 3 minutes to explain their research topic to a broad public.
GECCO 2022 (online) (Video)
Presenting our GENE paper at GECCO 2021. The video was pre-recorded.
Tsukuba University, Japan
Presenting my research on JEDi to Prof. Claus Aranha’s team at Tsukuba University.
Imperial College London, UK
Introduction presentation of my research to the AIRL lab at Imperial College London.
ISAE-SUPAERO, France
Presentation to an external jury composed of Prof. Nikolaus Hansen and Prof. Olivier Sigaud.
Research life contributions
I believe one's contribution to the scientific community also lies in the support and organization of research activities. Here are some of the ways I try to contribute:
Teaching
Elective module on evolutionary computation for students in their 1st year of MEng program. Teaching:
- Evolution Strategies
- Evolution of neural networks
- Genetic representation and operator design
- Quality-diversity approaches, evolution of behavior, coevolution
- Final project supervision: policy search for soft robots with ES
Teaching python to students in the FISA program and MSc in Aerospace Engineering:
- Basics of Python and algorithms
- 3D representation of planet movements
- Introduction to embedded systems with Micro:Bit
Introduction to Bash, Git and Python for students in the last year of the MEng. program.
OSS Contributions
Projects
Here are some of the recent projects I worked on, either during my PhD or my Masters degree, or as personal side projects.