About
The 3rd edition of Cosmo21 took place on 22-25 May 2018 in Valencia, Spain. During the week sessions were dedicated to machine learning, Bayesian methods, CMB and the statistics of fields, radio and intensity mapping, weak lensing, and surveys and statistics.
Conference Venue
The conference was hosted at ADEIT in Valencia, Spain.
SOC
Jean-Luc Starck (Chair, CEA Paris-Saclay)
Alan Heavens (Chair, Imperial College London)
Vicent Martinez (Chair, Valencia Observatory)
Vassilis Charmandaris (Nat. Obs. of Athens & Univ. of Crete)
Eric Feigelson (Penn State University)
Alberto Krone-Martins (Universidade de Lisboa)
Shirley Ho (Berkeley Lab, Carnegie Mellon University, Flatiron Institute)
Florent Leclercq (Imperial College London)
Valeria Pettorino (CEA Paris-Saclay)
María Pons-Bordería (Universidad Complutense de Madrid)
Elena Sellentin (University of Geneva)
David Spergel (Princeton University)
Licia Verde (Universitat de Barcelona)
Yanxia Zhang (National Astronomical Observatory)
LOC
Vicent Martinez (Valencia Observatory)
Samuel Farrens (CEA Paris-Saclay)
Pablo Arnalte-Mur (Universitat de Valencia)
Maria Pons-Bordería (Universidad Complutense de Madrid)
Cristina Mascarell (ADEIT, Fundació Universitat-Empresa)
Iulia Mich (ADEIT, Fundació Universitat-Empresa)
Nadia Lluna (ADEIT, Fundació Universitat-Empresa)
Keynote Speakers
Jo Dunkley (Princeton, USA), Cosmic Microwave Background
Jens Jasche (TUM, Germany), Large scale structures and Bayesian methodology
Stephanne Mallat (ENS, France), Deep learning theory
Rachel Mandelbaum (Carnegie Mellon University , USA), Weak lensing
Invited Speakers
Stefano Camera (Università degli Studi di Torino, Italy), Radio survey
Licia Verde (ICC, Spain), Systematics
Francois Lanusse (CMU, USA), Sparsity and machine learning in astrophysics
Michelle Lochner (AIMS, South Africa), Bayesian methodology in astrophysics
Elisabeth Krause (Stanford, USA), Dark Energy Survey, weak lensing and large scale structures
Peter Melchior (Princeton, USA), high-precision image analysis and statistical inference