Projects and PhD theses¶
Machine learning related projets at IN2P3 with their associated grants.
Please, add a new project through the form at this link.
Projects¶
Status
Domain
Improved Slitless Spectroscopy Analyses using Deep Learning
Euclid slitless spectrogram analyses using Deep Learning
Yannick CopinIP2I
JEDAI
Development of non supervised AI method for anomaly detection, application to ATLAS anomaly search in emerging jets
Sabine Crépé-Renaudin, Julien DoniniLPCA, LPSC
AstroDeep2
New machine learning techniques for the analysis of wide and deep, multi-color, multi-instrument, astronomical surveys
E. AubourgAPC, AIM
DeepTrack
Geometric deep learning for high-energy particle tracking
Alexis VallierL2IT
DIRECTA
Deep learning for CTA event reconstruction in real-time
T. VuillaumeLAPP
Acceleration of Atomic and Nuclear Structure Codes via Artificial Intelligence
Acceleration of Atomic and Nuclear Structure Codes via Artificial Intelligence
G. Hupin (Co-PI)IJCLab
AI for RF and Cryogenics in superconducting accelerators
AI for RF and Cryogenics in superconducting accelerators
A. GhribiGANIL
DIVE
DiHiggs In VBF Events : Exploring the Higgs boson properties through vector boson fusion HH production
L. CadamuroIJCLab, CPPM, LPNHE
ATRAPP
Advanced tracking algorithms for non-prompt tracks at the LHC
J. LévêqueLAPP, IJCLab
DISPERS
Deep learning for slit-less Spectroscopic Redshift survey Simulator
W. GillardCPPM
OGCID
Optimal graph convolution neural network for efficient particle identification
F. MagnietteLLR
PGTI: Prompt Gamma Time Imaging
NN pour calculer la dose de radiation recue par un patient à partir des données d'imagerie médicale en photonthérapie
S. MarcatiliLPSC, CPPM
DMwithLLPatLHC
Dark Matter with Long Lived Particles at LHC
M.-H. GenestLPSC, LPNHE, LPTHE
AMORCE InM4CAST
A. GhribiGANIL
ARTIFACT
A. GhribiGANIL
Investigating Diffusion Models for Astronomical Image Deconvolution
Investigating Diffusion Models for Astronomical Image Deconvolution
A. Boucaud, M. Huertas-CompanyAPC
Unbinned Deconvolution for Particle/Nuclear Physics
Unbinned Deconvolution for Particle/Nuclear Physics
A. ButterLPNHE
Data Science Methods and Tools to Exploit LHC Results
Data Science Methods and Tools to Exploit LHC Results
S. KramlLPSC
FIDDLE
Finding Invisible Decays with Deep Learning at Belle II
G. DujanyIPHC
Finding the first generation of stars with LSST
Finding the first generation of stars with LSST
Emille IshidaLPC-Clermont
ML for photometric redshift estimation in DESC
ML for photometric redshift estimation in DESC
S. MeiAPC
AIDAQ
Artificial Intelligence on FPGAs: A breakthrough for Data AcQuisition in High Energy Physics experiments and beyond
G. AadCPPM
ANN4EUROPE Franco-German AI grant
V. Gligorov (co-PI)LPNHE
H2020 AIDAINNOVA
H. GraslandIJCLab
Learning from deep sea light with KM3NeT
Learning from deep sea light with KM3NeT
J. CoelhoAPC
MSCA SMARTHEP MSCA ITN
V. Gligorov, B. MalaescuLPNHE
RICOCHET
Interdisciplinary project aimed at developing new tools and methods for the analysis, measure, characterization and simulation of the gravitational wave polarization
E. Chassande-MottinAPC, Gipsa-lab
Various activities around the search for hidden information in AGN data and in boosting sensitivity in gamma-ray and neutrino telescopes
Various activities around the search for hidden information in AGN data and in boosting sensitivity in gamma-ray and neutrino telescopes
Y. BecheriniAPC
Artificial Intelligence on FPGAs: A breakthrough for Data AcQuisition in High Energy Physics experiments and beyond (AIDAQ)
Artificial Intelligence on FPGAs: A breakthrough for Data AcQuisition in High Energy Physics experiments and beyond (AIDAQ)
G. AadCPPM
AstroDeep
Deep learning algorithms for galaxy deblending
E. AubourgAPC, CEA, Inria
DeepDIP
Deep Learning techniques for supernovae and photometric redshifts
D. FouchezCPPM, IAP, LAM, LIRMM, TETIS
Development of a gamma-camera for improved quantitative assessment of the heterogeneous distribution and biokinetics of 131I before and after treatment administration for thyroid diseases
Development of a gamma-camera for improved quantitative assessment of the heterogeneous distribution and biokinetics of 131I before and after treatment administration for thyroid diseases
Laurent MénardIJCLab
No project matches these filters.
PhD theses¶
To contribute new PhD theses, please fill the form at this link.
| Physics domain | Student name | Director name | Labs | Start year | End year | Funding | Short description | Associated project | Manuscript |
|---|---|---|---|---|---|---|---|---|---|
| ⚛️ | Laura Boggia | B. Malaescu | LPNHE | 2022 | 2025 | EU | Automate the learning of decision models by combining statistical and knowledge-based methods | - | |
| ⚛️ | Anthony Coreia | V. Gligorov | LPNHE | 2022 | 2025 | Franco German AI grant | Full reconstruction of charged particles in the LHCb detector using a graph neural network | - | |
| ⚛️ | Fotis Giasemis | V. Gligorov, B. Granado | LPNHE | 2022 | 2025 | EU (MSCA) | Charged Particle Reconstruction using Neural Networks on heterogenous architectures | - | |
| ⚛️, 🔭 | Enzo Oukacha | Y. Becherini | APC | 2022 | 2025 | Université Paris Cité | Search for neutrino-gamma correlations in the extragalactic sky | - | |
| ⚛️, 🔭 | Santiago Peña Martínez | A. Kouchner, J. Coelho | APC | 2022 | 2025 | STEP'UP | Deeply Learning from Neutrino Interactions with the KM3NeT neutrino telescope | - | |
| 🔭 | Lucas Sauniere | S. Escoffier, W. Gillard | CPPM | 2022 | 2025 | AMU | Instrument model for the NISP Slit-Less spectroscopy | - | |
| 💫 | Emmanuel Gouttière | Johanne Cohen, Hayg Guler | IJCLab | 2020 | 2024 | . | Utilisation de Méthodes d’Apprentissage pour la Modélisation d’un Accélérateur de Particules | ||
| 🔭, ⚛️ | Michaël Dell'aiera | T. Vuillaume, A. Benoit | LAPP, LISTIC (USMB) | 2021 | 2024 | ESCAPE, EOSC Future, LAPP | Deep Unsupervised Domain Adaptation for the Cherenkov Telescope Array | - | |
| ⚛️ | Guillaume Albouy | M.-H. Genest, P-A Delsart | LPSC | 2021 | 2024 | ED | Calibration en énergie et masse des jets hadroniques avec un DNN | - | |
| ⚛️ | Federico Nardi | J. Donini, T. Dorigo | LPC, INFN (Padoue) | 2021 | 2024 | EU, INFN | End-to-end optimization of experimental design with automatic differentiation | - | |
| 🔭 | Vincent Duret | S. Escoffier, W. Gillard | CPPM | 2021 | 2024 | AMU | Photometric redshifts calibration and cosmological constraints by tomographic galaxy clustering | - | |
| ⚛️ | Maxime Fernoux | A. Duperrin, E. Petit | CPPM | 2021 | 2024 | CNRS | Preparation of the Higgs boson self-coupling measurement in HH -> bbyy channel with ATLAS | - | |
| 🔭 | Biswajit Biswas | E. Aubourg, C. Roucelle, J. Lao | APC, Google | 2021 | 2024 | COFUND | Deep generative networks for probabilistic source separation | - | |
| 🔭 | Kirill Grishin | S. Mei | APC | 2021 | 2024 | Université Paris Cité | Cluster detection with machine learning and their galaxy population | - | |
| 🔭 | Justine Zeghal | E. Aubourg, A. Boucaud, F. Lanusse | APC, AIM | 2021 | 2024 | STEP'UP, diiP | Accelerating simulation-based inference (SBI) with differentiable simulators | - | |
| ⚛️ | Nemer Chiedde | E. Monnier, G. Aad | CPPM | 2020 | 2023 | CNRS | Implementation of embedded artificial algorithms on the backend readout boards of the ATLAS liquid argon calorimeter | Link | |
| ⚛️ | Lauri Laatu | E. Monnier, G. Aad | CPPM | 2020 | 2023 | AMIDEX, ANR AIDAQ | Development of artificial intelligence algorithms adapted to big data processing in embedded (FPGAs) trigger systems | Link | |
| ⚛️ | Arnaud Maury | D. Rousseau | IJCLab | 2020 | 2023 | UDOPIA | Simulation-Based Inference for the off-shell Higgs decaying into 4 leptons in ATLAS experiment | - | |
| ☢️ | Théo Bossis | Laurent Ménard | IJCLab | 2020 | 2023 | ED PHENIICS | Développement et évaluation d'un imageur gamma ambulatoire pour radiothérapie interne | - | |
| ⚛️ | Alexandre Hakimi | Jean-Baptiste Sauvan | LLR | 2019 | 2022 | . | Recherche de la diffusion de boson vecteur dans le canal semi-leptonique avec le détecteur CMS et études sur la classification de gerbes électromagnétiques avec HGCAL | https://theses.hal.science/tel-04106669 | |
| ⚛️ | Louis Vaslin | Julien Donini | LPCA | 2019 | 2022 | . | Recherche de Nouvelle Physique avec l'expérience ATLAS en utilisant des techniques de Machine Learning non supervisées et semi-supervisées | ||
| ⚛️ | Ioan Dinu | J. Donini, Alexa C. | LPC, IFIN-HH | 2019 | 2022 | IFIN-HH | New Small Wheel Muon Detector Trigger Processor Hardware and Beyond Standard Model Searches | - | |
| ⚛️ | Etienne Fortin | E. Monnier, G. Aad | CPPM | 2019 | 2022 | CNRS, Region PACA | Commissioning and performance of the trigger and readout system of the liquid argon calorimeter of ATLAS | Link | |
| ⚛️ | Louis Vaslin | J. Donini, V. Barra | LPC, LIMOS | 2019 | 2022 | University Clermont Auvergne | Recherche de Nouvelle Physique avec l'expérience ATLAS en utilisant des techniques de Machine Learning | - | |
| 💫 | Mathieu Debongnie | Jean-Marie de Conto, Frédéric Bouly | LPSC | 2017 | 2021 | . | Etude de la modélisation des accélérateurs de particules par des méthodes de «machine learning» pour optimiser et fiabiliser l'opération d'un linac de forte puissance | https://theses.hal.science/tel-03497446 | |
| ⚛️ | Lucas Torterotot | Colin Bernet | IP2I | 2018 | 2021 | . | _ Recherche de bosons de Higgs supplémentaires de haute masse se désintégrant en paire de taus dans l’expérience CMS au LHC à l’aide du machine learning_ | https://theses.hal.science/tel-03500774 | |
| 🔭 | Bastien Arcelin | E. Aubourg, C. Doux, C. Roucelle | APC | 2018 | 2021 | STEP'UP, ANR AstroDeep | Deblending galaxies with variational autoencoders | Link | |
| ⚛️ | Aishik Ghosh | David Rousseau | LAL | 2017 | 2020 | . | Simulation du calorimètre électromagnétique de ATLAS à l'aide de réseaux antagonistes génératifs et mesure au LHC des couplages du boson de Higgs hors résonance par inférence sans fonction de vraisemblance | https://theses.hal.science/tel-03324250 | |
| ⚛️ | Jonas Rembser | Philippe Busson | LLR | 2017 | 2020 | . | Mesure de la production de trois bosons massifs et identification des électrons avec le détecteur CMS auprès du LHC | https://theses.hal.science/tel-03720899 | |
| ⚛️ | Aishik Ghosh | D. Rousseau | IJCLab | 2017 | 2020 | ED | Simulation of the ATLAS electromagnetic calorimeter using GANs and likelihood-free inference of Higgs couplings | Link | |
| ⚛️ | Fabricio Jiménez | Julien Donini | LPCA | 2016 | 2019 | . | Model independent searches for New Physics using Machine Learning at the ATLAS experiment | https://theses.hal.science/tel-02402488 | |
| ⚛️ | Ziyu Guo | Cristinel Diaconu, Thierry Artières, Yann Coadou | CPPM | 2016 | 2019 | Aix Marseille Université | Recherche du boson de Higgs dans le canal ttH (H->bb) avec l'experience ATLAS auprès du LHC avec des méthodes d'apprentissage automatique et synchonisation de la description de la géométrie de l'ITk pour la simulation et les études de radiation de la jouvence d'ATLAS pour le HL-LHC | https://theses.fr/2019AIXM0350 | |
| 🔭 | Etienne Russeil | Emille Ishida, Emmanuel Gangler | LPC | 2021 | 2024 | TBD | Feature engineering and machine learning for 21st century astronomy | https://theses.fr/2024UCFA0102 | |
| ⚛️ | Léonard Imbert | Frédéric Yermia, Benoit Viaud | Subatech | 2021 | 2024 | TBD | Deep learning methods and Dual Calorimetric analysis for high precision neutrino oscillation measurements at JUNO | https://theses.fr/2024NANU4048 | |
| ⚛️ | Charline Rougier | Jan Stark, Catherine Biscarat | L2IT (Laboratoire des 2 infinis - Toulouse) | 2020 | 2023 | Université de Toulouse | _Trajectographie de particules chargées à l’aide d’un nouvel algorithme d’apprentissage géométrique profond et recherche de particules supplémentaires de type boson de Higgs dans les données d’ATLAS Run 2 _ | https://utheme.utoulouse.fr/s/fr/item/45951 | |
| ⚛️ | Fabricio Jimenez | J. Donini | LPC | 2016 | 2019 | EU | Model independent searches for New Physics using Machine Learning at the ATLAS experiment | - |
| Physics domain | Student name | Director name | Labs | Start year | End year | Funding | Short description | Associated project | Manuscript |
|---|---|---|---|---|---|---|---|---|---|
| 🔭 | Matthieu Thomeer | Yannick Copin | IP2I | 2025 | 2028 | CNES + ANR | Euclid slitless spectrogram analyses using Deep Learning | ||
| 🔭 | Adam Trigui | Mickael Rigault | IP2I | 2025 | 2028 | ANR | Simulation based inference for SN Cosmology | SCinf | |
| ⚛️ | Zirui Liu | David Rousseau | IJCLab | 2024 | 2027 | CSC | Study of double Higgs production in ATLAS in the bb-gamma gamma channel with Neuro Simulation Based Inference | ||
| ☢️ | Brigitte Pertille-Ritter | Matthieu Lebois | IJCLab | 2023 | 2026 | . | Développement de méthode innovantes basées pour la construction d'un trigger de fission | ||
| ⚛️ | I. Mozun Mateo | A. Vacheret, B. Guillon | LPC Caen | 2023 | 2026 | Chaire d'excellence ALPHA, région Normandie | Towards a high sensitivity measurement of tau neutrinos using novel machine learning techniques and Bayesian methods at KM3NeT/ORCA | ||
| ⚛️ | Raphael Bertrand | G. Aad, E. Monnier | CPPM | 2023 | 2026 | CNRS | Développement d'algorithmes d'intelligence artificielle embarqués pour le calorimètre à argon liquide ATLAS | - | |
| ⚛️, ☢️ | Dunstan Becht | N. Pillet, P. Indelicato, G. Hupin | CEA, IJCLab, LKB | 2023 | 2026 | Sorbonne Université | Convergence Acceleration for Atomic and Nuclear Structure Codes by Artificial Intelligence | - | |
| ⚛️ | Ragansu Chakkappai | D. Rousseau | IJCLab | 2023 | 2026 | ChaLearn | Uncertainty aware Artificial Intelligence for Higgs Cross-section measurement in ATLAS | - | |
| ⚛️, 🔭 | Max Eff | Y. Becherini | APC | 2023 | 2026 | Université Paris Cité | AI-based data analysis to unveil HESS faintest sources and search for astrophysical neutrinos in KM3NeT | - | |
| ⚛️ | Eva Mayer | J. Donini, S. Calvet, M. Michel | LPC, LMBP | 2023 | 2026 | ED | Development of statistical learning methods for the search of new physics signatures in ATLAS | - | |
| ⚛️ | Leonardo Splendori | T. Strebler, A. Duperrin | CPPM | 2023 | 2026 | CNRS | Probing the Higgs boson pair production through Vector Boson Fusion at ATLAS | - | |
| ☢️ | Brigitte Pertille | Matthieu Lebois | IJCLab | 2023 | 2026 | ED PHENIICS | Development of innovative methods for a fission trigger construction | - | |
| ⚛️ | Jeremy Couthures | Marco Delmastro, Alexis Vallier, David Rousseau | LAPP, L2IT, IJCLAB | 2022 | 2026 | CNRS | Development of new Machine Learning-based reconstruction algorithms for charged particle tracks in the ATLAS Experiment | ATRAPP | https://theses.fr/s349586 |
| 💫 | Marceau Pintonato | Sophie Kazamias, Kevin Cassou, Moana Pittman, Sébastien Coudreau | IJCLab | 2025 | 2028 | CIFRE | Development of advanced controls for a high-intensity laser driver for laser–plasma accelerators | https://theses.fr/s413316 | |
| 💫 | Mykyta Lenivenko | Fabian Zomer, Kevin Cassou | IJCLab | 2024 | 2027 | TBD | Optimizing Laser-Plasma Accelerators through Machine Learning | https://theses.fr/s397951 | |
| ⚛️ | Matthieu Melennec | Frédéric Magniette | LLR | 2023 | 2026 | TBD | Optimal graph convolution neural networks for efficient particle identification | OGCID | https://theses.fr/s370216 |
| ⚛️ | Andres Duque Bran | Julien Donini, Samuel Calvet, Vincent Barra | LPCA | 2024 | 2027 | University | Anomaly Exploration in the Search for New Physics at the LHC: Development of Learning Algorithms & Application to ATLAS Data | JEDAI | |
| ⚛️ | Melvyn Wirawan | Julien Donini, Samuel Calvet | LPCA | 2025 | 2028 | ANR | Searching for new physics with ATLAS experiment using machine learning-based anomaly detection | JEDAI | |
| ⚛️ | Warren Guérin | Alexis Vallier | L2IT | 2024 | 2027 | Université de Toulouse | Study of Higgs boson self-coupling in the HH→bbγγ channel using geometric deep learning techniques and the ATLAS experiment at the LHC collider at CERN. | ||
| ⚛️ | Guillem JOSEPH PLANAS | Alexis Vallier | L2IT | 2026 | 2029 | ANR | Study of the Higgs boson and its self-coupling in the H → γγ and HH → bbγγ channels using deep learning techniques and the ATLAS experiment at the LHC collider at CERN. | DeepTrack | |
| ⚛️ | Thomas PAUL | Sabine Crépé-Renaudin, Pierre-Antoine Delsart | LPSC | 2026 | 2029 | JEDAI (MIAI Cluster UGA) | Anomaly detection with developments of non supervised IA method, application to emerging jet search in ATLAS | JEDAI |