Research Interest numerical climate modeling at global scale machine learning, physics informed machine learning hybrid physics and AI-based modeling heterogeneous (mixed GPU and CPU-based) high performance computation Education 2022-present: research scientist. Machine learning for climate modeling, CNRM (Toulouse). 2019-2022: PhD. « Vers une utilisation de l’Intelligence Artificielle dans un modèle numérique de climat ». INP Toulouse. PhD advisors: David Saint-Martin, Aurélien Ribes. 2016-2019: École Nationale de la Météorologie, cycle ingénieur (Toulouse). 2014-2016: CPGE (Paris).
2025 Germain, H., Balogh, B., O. Geoffroy, and D. Saint-Martin, 2025: Improvment of a neural network convection scheme by including triggering and evaluation in present and future climates. Preprint available on arXiv:2511.05074. Balogh, B., D. Saint-Martin, and O. Geoffroy, 2025: Online Test of a Neural Network Deep Convection Parameterization in ARP-GEM1. Artif. Intell. Earth Syst., 4, e240100, https://doi.org/10.1175/AIES-D-24-0100.1. 2022 Balogh, B., Saint-Martin, D., & Ribes, A. (2022). How to calibrate a dynamical system with neural network based physics ? Geophysical Research Letters, 49, e2022GL097872. https://doi.org/10.1029/2022GL097872 2021 Balogh, B., Saint-Martin, D., & Ribes, A. (2021). A toy model to investigate stability of AI-based dynamical systems. Geophysical Research Letters, 48, e2020GL092133. https://doi.org/10.1029/2020GL092133 Presentations & Conferences 2025 Balogh, B., Germain, H., Geoffroy, O. and Saint-Martin, D.: Climate Simulations with Online Neural Network-based Parameterization of Deep Convection: present and +4K. EXCLAIM! Symposium, Zürich, Swiss, 2-4 June 2025. Event website: https://exclaim-symposium.ethz.ch/ . 2024 Balogh, B., Saint-Martin, D., Geoffroy, O., Bhouri, M. A., and Gentine, P. : Assessment of ARPEGE-Climat using a neural network convection parameterization based upon data from SPCAM 5, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7455, https://doi.org/10.5194/egusphere-egu24-7455, 2024. 2022 Balogh, B., Saint-Martin, D., and Ribes, A. : How to calibrate a climate model with neural network based physics ?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7135, https://doi.org/10.5194/egusphere-egu22-7135, 2022. 2021 Balogh, B., Saint-Martin, D., and Ribes, A. : A toy model to investigate stability of AI-based dynamical systems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-647, https://doi.org/10.5194/egusphere-egu21-647, 2021.
Internships 2026. Offre de stage de M2 (6 mois) : utilisation de techniques d’IA génératives pour la modélisation de la convection profonde dans ARP-GEM. 2025. Stage de M2 (6 mois), Hugo Germain (ENM, Toulouse). Amélioration d’une paramétrisation IA de la convection profonde dans ARP-GEM.
