This is the fourth edition of the annual ESAC Data Analysis and Statistics (EDAS) Workshop.

This four-day EDAS workshop will take place from Tuesday November 28 to Friday December 1 at the European Space Astronomy Centre near Madrid in Spain.

Two days will cover fundamental topics in statistics and data analysis, and two days will be for practical applications and more advanced topics.

Each day of this year's EDAS workshop will be led by a different tutor. 

The tutors for this year are Doctors Brendon Brewer, Ewan Cameron, Coryn Bailer-Jones, and Michelle Lochner (details below).


Table of contents


Registration will be open until Friday 27 October 2017. A contribution from external participants of 75 euros must be paid in cash on the first day of the workshop when picking up your name tag. The number of participants will be limitted to 80. A selection process will take place if more than 60 submit a registrationTo register click here.


​Dr Brendon Brewer 

is a senior lecturer in statistics at the University of Auckland in New Zealand. His PhD was in astrophysics and he has worked on inference problems in gravitational lensing, reverberation mapping, asteroseismology, and cricket. His methodological interests are in computational Bayesian inference, with a focus on the Nested Sampling family of algorithms. (See also and



Dr Ewan Cameron   

is a senior computational statistician in the Malaria Atlas Project team at the University of Oxford. His work is focused on the development of novels methods for probabilistic map making and the calibration of expensive simulation-based models for disease transmission, both of which are founded on fast and flexible techniques for Gaussian process regression. Dr Cameron has a background in the study of galaxy evolution and post-doctoral experience in the study of Bayesian methods applied to astronomical datasets. He also maintains an active interest in astrostatistics through his blog and his involvement with the Cosmostatistics Initiative. (See also and


Dr Coryn Bailer-Jones   

is a senior staff member and group leader at the Max Planck Institute for Astronomy in Heidelberg. He is head of Coordination Unit 8 in the Gaia Data Processing and Analysis Consortium (DPAC). CU8 is concerned with source classification and the estimation of astrophysical parameters using Gaia photometry, spectroscopy, and astrometry. His main scientific interests are stars, the Galaxy, and the impact of astronomical phenomena on the Earth. He also teaches physics and statistics at Heidelberg University. His book "Practical Bayesian Inference" was published in 2017 by Cambridge University Press. (See also



Dr Michelle Lochner   

is a Resident Researcher at the African Institute for Mathematical Sciences (AIMS) and the Square Kilometre Array South Africa (SKA SA). She did her PhD at the University of Cape Town before moving to University College London for a two-year postdoc. She has now returned to South Africa to take up the position she currently holds. Her broad interest is in developing new techniques that enable precision cosmology, and she has worked on statistical and machine learning applications in the fields of supernova cosmology, radio interferometry and radio spectroscopy. As an active member of two of the most exciting upcoming astronomical experiments, LSST and the SKA, she is passionate about the role statistics and machine learning can play in extracting the most out of the incoming "mega data" we'll be seeing in the near future. (See also





Tuesday 28 November

The Bayesics. Session led by Dr Brendon Brewer, topics include: 

  • Probability theory
  • Probability distributions
  • Bayesian inference & parameter estimation
  • Metropolis algorithm
  • Mythbusting

Wednesday 29 November

Advanced Bayesian computation. Session led by Dr Ewan Cameron, topics include: 

  • Model checking
  • Prior regularisation
  • Model design
  • Model ensembles

Thursday 30 November

Applications to GAIA. Session led by Dr Coryn Bailer-Jones, topics include:

  • Single objects - astrometry & photometry based parameter estimation
  • Multi-object - inter-source covariance, selection function, hierarchical modelling 
  • Priors from background information

Friday 1 December

Machine Learning in astronomy. Session led by Michelle Lochner, topics include:

  • Introduction to machine learning
  • Machine Learning vs Statistical methods
  • Classification
  • Post processing 


The workshop and hands-on sessions will be based on python 3.

Attendees are expected to come to the workshop with the following requirements in order to participate in the hands-on sessions:

We recommend the all-in-one scientific Python installer Anaconda. Download Anaconda from

Science Organising Committee

  • Guillaume Belanger (chair)
  • Michele Armano
  • Alex Bombrun
  • Felix Fuerst
  • Maggie Lieu
  • Marcos Lopez
  • Luis Mendes
  • Bruno Merin
  • Luis Manuel Sarro
  • Hassan Siddiqui
  • Ivan Valtchanov
  • Roland Vavrek
  • Japheth Yates

Local organising committee

  • Ana Willis (chair)
  • Guillaume Belanger
  • Felix Fuerst
  • Maggie Lieu
  • Marcos Lopez
  • Bruno Merin
  • Luis Mendes
  • Ivan Valtchanov
  • Roland Vavrek
  • Japheth Yates

Funding and IT support

This workshop is fully funded by the ESAC Science Faculty. IT support was provided by Cosmos team.