Debating the potential of machine learning in astronomical surveys

Important dates

October 18-22 2021, IAP, Paris

Deadline for abstract submission: August 30th 2021

Deadline for registration: October 17th 2021

Scientific rationale

The 2021 IAP colloquium is dedicated to a critical analysis of Machine Learning methods in astronomy.

A major revolution is now underway in astrophysics with the constant arrival of ever-richer and more complete datasets. The next generation of surveys soon starting will generate orders of magnitude more data than previously. However, it is becoming increasingly clear that traditional techniques are not up to the challenge of fully exploiting these data. At the same time, in the computer industry, large-scale application of “machine learning” methods on large quantities of data have been able to solve problems that until now have been intractable. These new techniques are now being adopted enthusiastically by astronomers who see them as a way to extract the maximum amount of science from new surveys.  However, some caution is required; the concerns of industrial players developing machine learning techniques are not the same as astrophysicists who seek to explain observations in the framework of physical models. It is therefore very timely to survey the landscape of machine-learning techniques in astronomy and to critically evaluate their usefulness for solving astrophysical problems. At IAP, many advanced analysis techniques have been pioneered to analyse data from the Planck satellite and from ground-based surveys; the avalanche of rich datasets coming from future missions like Euclid and ARIEL makes the institute a natural location to hold this conference.

The conference will explore the potential and applicability of machine learning techniques for future surveys such as DESI, SKA, Euclid, Rubin Observatory, Ariel and Gaia. In particular the impact of systematic errors on the reliability of inferred parameters (cosmological or otherwise) derived using these methods will be explored. The ability of machine-learning models to lead to scientific discoveries will be critically discussed.

The IAP international colloquia, organised every year since 1985, brings together scientists from around the world. These meetings are a unique opportunity for students and postdocs in the Ile-de-france to meet and interact with specialists. This year's conference, to be held in October, will include the possibility of in-person attendance for a small number of people but the meeting will be largely online. Despite this, significant time will be set aside in the program so that all participants can interact through debates and round-table discussions.

Invited reviewers and panellists

Invited reviewers:

  • Michelle Lochner
  • Gilles Louppe
  • Francisco Villaescusa-Navarro
  • Ingo Waldmann
  • Benjamin D. Wandelt
  • Elisabeth Krause 

Invited panellists:

  • Anastase Charantonis
  • Tom Charnock
  • Torsten Ensslin
  • Chiara Ferrari
  • Rémi Flamary
  • Alan Heavens
  • Marc Huertas-Company
  • Shirley Ho
  • David Hogg
  • Bhuvnesh Jain
  • Jens Jasche
  • Francois Lanusse
  • Brice Menard
  • Hiranya Peiris
  • Laurence Perreault Levasseur
  • Alexandre Refregier
  • Romain Teyssier
  • Licia Verde

Participations costs

Given the hybrid structure of thee meeting, we adopted the following registration fees.

  • 50 euros for remote participation
  • 100 euros for on-site student attendance
  • 200 euros for on-site standard fee

The choice from remote to on-premises participation may be made later depending on needs.


Scientific Organizing comittee:

  • Anastase - Alexandre Charantonis
  • Karim Benabed
  • Torsten Ensslin
  • Shirley Ho
  • David Hogg
  • Marc Huertas-Company
  • Guilhem Lavaux
  • Henry Joy McCracken
  • Brice Ménard
  • Hiranya Peiris
  • Sylvie Thiriat
  • Licia Verde
  • Benjamin D. Wandelt
  • Ingo Waldmann


Local Organizing comittee:

  • Sandy Artero
  • Karim Benabed
  • Valérie Bona
  • Chotipan Boonkongkird
  • Etienne Camphuis
  • Guilhem Lavaux
  • François Lanusse
  • Henry McCracken
  • Marko Shuntov



Credit image: Jean Mouette (IAP)

We acknowledge the financial support of the following agencies, institutes and national initiatives :

Code of conduct

All participants must follow the IAU Code of Conduct:

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