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Statistical Challenges in 21st Century Cosmology (COSMO21)

The dialogue between astronomers and statisticians during the last 20 years has been fruitful and has been the origin of a new discipline that is now widely called Astrostatistics. In addition to actual data challenges, the cosmological community is preparing big surveys such as LSST, Euclid and SKA. These examples highlight the big current role and even bigger future role of archival data in astrophysics research.
When 23 May 2018 05:35 PM to
25 May 2018 05:35 PM
Where Valencia ES
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Keynote speakers

  • Cosmic Microwave Background Jo Dunkley (USA / Princeton)

  • Bayesian Methodology Jens Jasche (Germany / TUM)

  • Deep Learning Stephane Mallat (France / ENS)

  • Weak Lensing Rachel Mandelbaum (USA / Carnegie Mellon)

  • Gravitational Waves Samaya Nissanke (The Netherlands / Radboud Uni-


    Invited speakers
    Radio Survey Stefano Camera (Italy / Torino Univ)
    Intensity Mapping Tzu-Ching Chang (USA / JPL)
    Machine Learning Francois Lanusse (USA / CMU)
    Bayesian Methodology Michelle Lochner (South Africa / AIMS) Large scale structures Elisabeth Krause (USA / Stanford)


  • Cosmic Microwave Background, Weak lensing, Large scale structure, High redshift supernovae, Mapping high-z 21-cm radiation, Lyman-alpha forest, Gravitational waves

  • Astronomical discovery from overwhelmingly large datasets

  • Statistical methods used in astronomical data analysis, e.g.: Bayesian

    methods: evidence, model selection, multivariate classiYication and cluste- ring; Sparsity: wavelets, compressive sampling; Machine learning 

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