Special Session SS21  27 June 2022

Stellar characterization, large data sets, and Machine Learning

Aims and scope

During the last 15 years, the development of space, ground-based facilities, and projects for collecting large data sets have opened a new era in astrophysics. Gaia (ESA), Kepler (NASA), TESS (NASA), CoRoT (ESA), APOGEE, etc., are only some examples. This explosion has been coincident with the expansion of data analysis tools in the Big Data domain, generating the perfect context for extracting the most information possible from these data sets.

This has supposed a revolution in stellar characterization in particular, with deep benefits for different topics such as galactic archeology, exoplanets characterization, stellar structure and evolution studies, etc. The scientific community is currently very active on this topic, with more than fifty papers published in this field in peer-reviewed journals since 2020. The Special Session we are proposing aims to be a milestone in this field, a shared space for this young and very active community. In particular, the main goals of this session are:

  • To offer a summary of the state-of-the-art for Machine learning in the context of stellar characterization, with special attention to uncertainty quantification.
  • Presenting new tools for analyzing the data and promising new research lines.
  • Presenting the most recent results, works, and projects in the context of Stellar characterization, large data sets, and Machine Learning/AI.
  • To offer a space for new contacts, collaborations, networking, among the different researchers interested in this topic.


    • Large data sets
    • Machine Learning/AI techniques for stellar characterization
    • Characterizing stars (masses, ages, radii, temperatures, ...)

    Invited speakers

    • René Andrae (Max-Planck-Institute for Astronomy, DE)
    • Rafaél García (CEA Saclay, FR)
    • Cristina Chiappini (Leibniz-Institut für Astrophysik Potsdam - AIP, DE)
    • Cecilia Garraffo (Center for Astrophysics, Harvard & Smithsonian , USA)

    Scientific organisers

    • Earl Bellinger (SAC - Aarhus University, DK)
    • Lisa Bugnet (Flatiron Institute, USA)
    • Guy Davies (University of Birmingham, UK)
    • Savita Mathur (IAC, SP)
    • Andrea Miglio (University of Bologna, IT)
    • Joey Mombarg (KU Leuven, BE)
    • Andy Moya (University of Valencia, SP, Chair)
    • Juan Carlos Suárez (University of Granada, SP)


    andres.moya-bedon  @  uv.es

    Updated on Sat Feb 26 22:22:04 CET 2022