• WP leader in the project Taranis of the PEPR Cloud
  • WP leader in the ANR project SeMaFoR

PEPR Cloud (2023-2030)

OTPaaS project (2021-2024)

The OTPaaS French project aims at offering a new Cloud offer, compatible with Gaia-X and easy to use, that could favour the massive digital transition of companies.

SeMaFoR project (2020-2024)

The SeMaFoR project (ANR PRCE), for Self Management of Fog Resources, is funded by the French national research agency for 4 years. The project is led by Thomas Ledoux. I am the leader of the third work package of this project to handle decentralized reconfiguration when coordinating multiple control loops.

Former projects:

  • Lowcomote Lowcomote is a European project that aims to train a generation of professionals in the design, development and operation of new LCDPs, that overcome the limitations above, by being scalable (i.e., supporting the development of large-scale applications, and using artefacts coming from a large number of users), open (i.e., based on interoperable and exchangeable programming models and standards), and heterogeneous (i.e., able to integrate with models coming from different engineering disciplines). These scientists will drive the upgrade of the current landscape of Low-Code Development Platforms to Low-Code Engineering Platforms (LCEPs).
  • VeRDi project funded by the French region Pays De La Loire where Nantes is located. VeRDi is an acronym for Verified Reconfiguration Driven by execution. It aims at addressing distributed software reconfiguration in an efficient and verified way.
  • PIA FSN Hydda that aimed to develop a software solution allowing the deployment of Big Data applications (with hybrid design (HPC/CLoud)) on heterogeneous platforms (cluster, Grid, private Cloud) and the orchestration of computation tasks (like Slurm, Nova for OpenStack, or Swarm for Docker).
  • The Discovery inria project lab



Concerto is a preliminary implementation in Python 3 of the Concerto reconfiguration model.

Madeus Application Deployer (MAD)

MAD is a PYTHON implementation of the Madeus model on top of Concerto. Its purpose is to offer a way to define a low-level deployment process and coordinate this deployment in an efficient and reliable manner. MAD is low-level but offers a highly generic deployment model.

The SkelGIS Library

The SkelGIS Library has been developed during my Ph.D. SkelGIS is a C++-embedded domain specific language for numerical simulations based on explicit schemes. SkelGIS has been implemented for 2D Cartesian meshes and for network of Cartesian meshes. It also has been evaluated on two real case numerical simulations. I am for now the only contributor of the Library, however it is no longer maintained. You can download sources here.

SkelGIS video: basic demo

SkelGIS video: Malpasset real use case