In September 2022, I joined the PSL’s AI teaching team as an AI Fellow, with a teaching duty of 150 h/year, mainly for master’s and graduate programs.
See EFELIA and PSL’s cross-disciplinary Data Science program for more information.
PhD Jury member and committee
– PhD monitoring committee member for W. Tenachi – Strasbourg Observatory, FR (2023)
– Examinator for R. Poitevineau’s defense – Paris Observatory, FR (2023)
– Invited (as an external co-supervisor) for Nina Kessler’s defense – LAB, Bordeaux, FR (2025)
Also, examiner for several M2 internship defenses
PhD Courses
– AI for Astrophysics, yearly since 2024, AAIF doctoral school (ED 127), Paris, FR. Full-week course.
Summer Schools / Intensive Weeks / Short interventions
– [Upcoming 10/2025] – MARI, giving a class on Deep-Learning for source detection in radio-astronomical data, Université de Strasbourg.
– PSL Week – « Green AI, » yearly since 2024, full organization, responsibility, and all lessons and resources.
– ESPCI 3A Deep-Learning for object detection masterclass, yearly since 2023, ESPCI, Paris, FR, resources.
– Machine Learning – YOLO architecture tutorial, 09/2022, website, link to resources, ITI IRMIA++, Strasbourg (with ObAS), FR
Master Courses
– M2 – Introduction to Machine Learning, yearly since 2024, Paris Observatory, M2-OSAE, mandatory course for all students.
– 1A – « Green AI » through computation efficiency, yearly since 2024, ESPCI, resources.
– M2 – Machine Learning for astronomical data, yearly since 2022, Paris Observatory, M2-OSAE, part of the numerical recipes specialty course, Link to course resources (in English).
– M2 – Numerical methods: Machine Learning and Artificial Neural Networks, 2018 to 2020, Univ. Franche-Comté, Master P2N – CompuPhys (Computational Physics).
– M2 – Numerical methods: High-Performance Computing (OpenMP, MPI, CUDA, …), 2018 to 2020, Univ. Franche-Comté, Master P2N – CompuPhys (Computational Physics) and PICS (from FEMTO-ST).
– M1 numerical project, 2017, Univ. Franche-Comté, Master P2N – CompuPhys (Computational Physics), for two students on Artificial Neural Network usage and astrophysical applications.
« Licence » Courses (Bachelor)
– 2nd year (L2): Python programming and numerical recipes (linear systems solving, numerical integrator, ordinary differential equation), 2018-2019, Univ. Franche-Comté, Physics and Mathematics bachelor.
High school interventions
– TalENS program of the Ecole Normale Superieure Paris, 2016-2017 Astrophysics introduction lessons and tutorship of a group of high school students. Link to the program webpage TalENS.
Supervision
As a PhD advisor:
– Adrien Anthore (starting 2025): Co-director with Laurent Chemin (OBAS), CPJ-ANR Funding.
– Adam Zarka (starting 2025): Principal director (OBSPM), PR[AI]RIE-PSAI funding (ANR/France2030).
– Nina Kessler (from 2022 to 2025): Co-advisor (LAB), AI doctoral program funding (ANR IA Bordeaux, France2030).
I was, and still am, participating in the supervision of other PhD theses more informally. Most of the time, these participations involve advice and support regarding the proper use of ML/AI methods in an astronomical context (e.g., Remi Poitevineau, Romain Meriot, and Kevin Luke).
Internship advisor:
– A. Anthore : Detection and characterization of galaxies in radio astronomical dataset with ML – M1 long Internship (01-06/2023) + M2 Lab Insertion Unit (09-12/2023) + M2 Internship (01-06/2024). Poster presented at the EAS 2024.
– R. Zouhhad : M2 Internship, Dig the Radio Sky with Neural Networks, details, 04-07/2022.