Team

Astrophysics meets data science

Project organisation

The Hyperstars collaboration is a combination of experts in astrophysics specialized in hyper-spectral data, interstellar dust modelling and numerical simulations of the star formation process, and experts in data science covering a large range of expertise: clustering, data mining, machine learning, data quality, inverse problem, source separation, and optimisation on GPU architecture. All participants of the project are in the Paris area.

Hyperstars received funds from Mastodons, an initiative of the Mission pour l'Interdisciplinarité du CNRS, and from DIM-ACAV+.

Team members

Laboratoire Astrophysique, Instrumentation et Modélisation (AIM), Université Paris-Saclay

  • Marc-Antoine Miville-Deschênes : CNRS directeur de recherche and scientific coordinator of Hyperstars. Analysis of astrophysics data applied to the star formation process.
  • Patrick Hennebelle : CEA scientist. Numerical simulations of the star formation process, from Galactic scales to proto-planetary disks.
  • Antoine Marchal : Ph. D. student working on a study of thermal instability of the atomic gas using a segmentation of hyperspectral 21 cm data.
  • Gerardo Ramon-Fox : Post-doc working on numerical simulations and synthetic observations of molecular clouds formation.

Institut d'Astrophysique Spatiale (IAS), Université Paris-Saclay

  • Nathalie Ysard : Chargée de recherche au CNRS. Modelling of dust emission and extinction. Radiative transfer.

Laboratoire des Signaux et Systèmes (L2S), CentraleSupelec, Université Paris-Saclay

  • Nicolas Gac : Maître de conférences at Université Paris-Sud. parallel computing, optimisation of code to GPU architecture.
  • François Orieux : Maître de conférences at Université Paris-Sud. inverse problems in the context astronomical data.
  • Charles Soussen : Professor at CentraleSupelec. source separation applied to hyper-spectral data in astronomy.

Laboratoire d’Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie

  • Marie-Jeanne Lesot : Maître de conférences. machine learning, data mining, clustering

Laboratoire d’Informatique Avancée de Saint Denis (LIASD), Université Paris-8

  • Adrien Revault d’Allonnes : Maître de conférences. data quality, information quality, clustering, big data processing