Machine Learning in Astronomy
David van Dyk (Imperial College)
Chris Arridge (Lancaster University)
Florent Leclercq (Imperial College)
Ingo Waldmann (University College London)
The Royal Statistical Society section on Statistical Computing, and the Lancashire and Cumbria local group, are organising a one-day workshop on Machine Learning in Astronomy. This workshop is focused on the growing area of research in Astrostatistics and the application and Machine Learning techniques to answer scientific questions in Astronomy and Cosmology. In recent decades there has been an enormous increase in the volume and complexity of recorded astronomical data. To answer the many important scientific questions posed by the astronomical community, there is a need to develop efficient and objective scientific tools to exploit multifaceted astronomical data sets and to link these to astrophysical theory. Ongoing work in this area has already led to new statistical methods and machine learning techniques for classifying galaxies, discovering new pulsars and detecting of exoplanets.
This workshop is a half-day event which aims to bring together academics and students interested in the research challenges that lie at the interface between Astronomy and Data Analysis. There will be a poster session and wine reception sponsored by the RSS local group at the end of the workshop.
Please note: The event is free to attend, but attendees must register for a ticket in advance.
13:00 - 13:15 - Opening and introductions
13:15 - 14:00 - David van Dyk (Imperial College)
14:00 - 14:45 - Chris Arridge (Lancaster University)
14:45 - 15:15 - Coffee break
15:15 - 16:00 - Florent Leclercq (Imperial College)
16:00 - 16:45 - Ingo Waldmann (UCL)
16:45 - 18:00 - Wine reception and poster session
This event is jointly organised by the Royal Statistical Society Statistical Computing Section, and the Royal Statistical Society Lancashire and Cumbria local group.