Commitees

Steering committees

co-organiser of DeMythif.AI a Université Paris-Saclay COFUND with 25 PhD on AI uncertainties (and application) who have started in fall 2024 and 2025
member of the executive committee of Université Paris-Saclay DataIA, the Artificial Intelligence Institute of Université Paris-Saclay
Associate editor for Computing and Software for the Big Science (CSBS) and now (Feb 2025) for European Physical Journal C
member of directorate of Chalearn, a US non-profit dedicated to data challenges organisation

Working Groups

member of Fair Universe, a LBNL Berkeley, U Washington, Chalearn collaboration organising two major scientific competitions Fair Universe HiggsML Uncertainties (NeurIPS 2024), Faire Universe Weak Lensing Uncertainty Challenge (NeurIPS 2025)
Scientific lead of CNRS/IN2P3 Machine Learning
co-lead IJCLAB “Calcul et données” (computing and Machine Learning)

Workshop and conferences

lead AISSAI thematic semester AI for Meta Science, with Institut Pascal workshop 23-27 Nov 2026
member of org committee School of Statistics, bi-yearly Statistics and Machine Learning IN2P3 school, last one in May 2026

Past responsabilities

Connecting The Dots is a yearly international workshop on particle tracking in High Energy Physics, last one CTD2025 in Tokyo, next one CTD 2027 in Frascati, I organised 2017 edition in Orsay
2021-2025 member of the CNRS Interdisciplinary Commission “Sciences et Données” CID 55 (Science and data, not data science !). In particular, this commission (now numbered CID 54) recruits yearly (calls opened in Dec) for permanent non-teaching positions a handful of junior scientists, and up to one senior scientist (all kind of physics, chemistry…), with a strong expertise in data science.
Hammers and Nails is a bi-yearly workshop on AI and physics held at Weizmann Institute, Israël ( in 2019, in Aug 2022)
2023 AISSAI IN2P3 thematic semester with several events, in particular AI and the Uncertainty Challenge in Fundamental Physics in Paris and Orsay 27 Nov-2 Dec 2023
2019-2022 Learning to discover is a series of three two-weeks workshop on the general theme of AI and physics held at Université Paris Saclay Institut Pascal. Check out the final one Apr 2022 !
2019-2022 co-lead Université Paris-Saclay Center for Data Science
2016-2022 co-organiser of the TrackML challenge : “Accuracy” phase on Kaggle, S. Amrouche et al. “The Tracking Machine Learning Challenge : Accuracy phase” in NeurIPS 2018 Competition Book arXiv 1904.06778, and “Throughput” phase on Codalab S. Amrouche et al. “The Tracking Machine Learning Challenge : Throughput phase” Comput. Softw. Big Sci. 7 (2023) arXiv 2105.01160
2018-2021 CERN LHCC Interexperiment Machine Learning group
2016-2018 : co-convenor ATLAS Machine Learning group
2013-2015 : co organiser of the Kaggle Higgs boson challenge ‘”HiggsML” “The Higgs boson machine learning challenge”, C. Adam-Bourdarios et al. JMLR42
2013-2016 : ATLAS team leader at LAL
2010-2012 : overall coordinator of Atlas offline software, which was a major tool for the Higgs boson discovery announced in July 2012. About 10 PetaBytes of real and simulated data analysed with 4 millions lines of code, written by a total of 1000 people over ten years (250 being active at any given point), and used by 1500 users (the experiment’ physicists).
1999 to 2010: coordinator of Atlas reconstruction software, master minding the algorithms developments and integration
2005-2006 : co-coordinator of Atlas liquid argon calorimeter software
2005-2013 : member of Computing Atlas France committee overseeing grid computing for Atlas in france
2004 : chair of Atlas persistent object task force
1999-2002 : coordinator of Inner Detector reconstruction software (tracking)