The Helios team
Helios spans several teams at CERFACS, as well as some outside collaborators.
Corentin Lapeyre is a research scientist at CERFACS in the COOP team. He supervises part of the research effort in Helios, and coordinates the exchanges in the Helios community.
Michaël Bauerheim is a Professor at ISAE-Supaéro in the DAEP department, and is involved in supervising Ph.D. students in Helios.
Laurent Terray is a senior scientist at CERFACS, and director of the joint CERFACS-CNRS Climate, Environment, Coupling and Uncertainties unit. He has extensive experience in climate modeling, and currently studies how data-driven methods can help to adress climate problems.
Mélanie Rochoux is a research scientist at CERFACS. She investigates several topics related to safety issues, and has been recently applying neural networks to forest fire front detections.
Sophie Ricci is a research scientist, with several reasearch topics in the fields of data assimilation and uncertainty quantification, and applications related to environmental issues such as water management and flood prevention.
Victor Xing joined the team in 2018 and is a Ph.D. student on deep learning for turbulent reactive flow modeling.
Ekhi Ajuria is a Ph.D. student working between ISAE-Supaéro and CERFACS on training neural networks to find approximate solutions to the Poisson equation.
Antonio Alguacil is a Ph.D. student working at ISAE-Supaéro and CERFACS on solving the wave equation using convolutional neural networks.
Luciano Drozda is a Ph.D. student working at CERFACS new uses of neural networks for the resolution of PDEs.
Victor Coulon is a Ph.D. student working at CERFACS on deep learning for turbulent hydrogen combustion modeling.
Dorian Dupuy is a postdoctoral fellow working on deep learning for wall friction prediction.
Anass Serhani is a postdoctoral fellow working on high performance optimization of hybrid CFD solvers using deep learning.
Théo Defontaine is a Ph.D. student using machine learning for flood forecasting.
Rachid El Montassir is a Ph.D. student working on physics-guided deep learning for cloud cover nowcasting.
Rémi Alas is a Ph.D. student working on deep learning approaches to atmospheric boundary layer modeling.
Valentin Mercier is a Ph.D. student working on deep learning techniques to accelerate hydraulic flow solvers.
Camille Besombes did his Ph.D. on deep learning for data assimilation.
Benjamin Sanderson was a research scientist at CERFACS, funded by a MOPGA award. He worked for several years with neural networks in the context of climate modeling, and looked into new appraoches based on Generative Adversarial Networks.
Elsa Gullaud was a post-doc at CERFACS in the COOP team, working on several data science and machine learning topics including to improve turbulent combustion models for large scale simulations in the context of fire safety studies, and to detect bears in an ecological setting with DREAL Occitanie.
Antony Misdariis was a research scientist in the CFD team at CERFACS, involved in the supervision of several Helios students.
Bastien Nony was an intern with Helios for the spring of 2019, working on data reconstruction methods for hydraulic applicaitons.
Aakash Patil was an intern with Helios for the spring of 2019, working on turbuelnce generation for injection in CFD codes.
Ronan Paugam was a post-doc at CERFACS in the GlobC team, working on forest fire modeling and risk assessment and making use of convolutional neural networks for forest fire flame front detection.
Nicolas Cazard was a research engineer working on developing tools for active learning and reuse of neural networks in physical solvers.
Laure Labarrère was a post-doc at CERFACS, working on developing the next generation of fluid solvers, based on a hydrid approach of classical equation solvers and deep-learning inference online.
Maxence Ronzié did his Masters internship in 2018 on deep learning for impact detection in Mars Reconnaissance Orbiter data.