Machine Learning and Artificial Intelligence applied to astronomy 2

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This meeting follows a successful meeting we ran in March 2019.  

Data sets in astronomy are becoming extremely large and complex. The research questions that are being asked of these data are also becoming complex and in many cases the richness of the data surpasses the level of sophistication of the theoretical models.  Machine learning and AI can thus be used to augment physical models for practical applications (e.g. photometric redshifts) or physical understanding (e.g. galaxy classification, model fitting).

The extreme data challenges arising from astronomy research could provide a very valuable environment  for developing the skills and techniques need outside astronomy.  They thus provide a potential route to socio-economic impact, important for the sustainability of the discipline. 

This meeting provides us with an opportunity to share  expertise and develop our skills in these important areas and explore where Astronomy pushes the boundaries of these techniques.

The meeting is open for registration and we welcome applications for talks from everyone.
Please register to attend or talk here


Seb Oliver (University of Sussex),

Stephen Serjeant (Open University)


More information to follow