My research interests

Machine learning in astronomy and astrophysics

  • Real-time ML/DL workflows for prioritisation and classification of astronomical objects.
  • Data-mining of transient streams, and value-added contextual information.
  • Bayesian deep learning for uncertainty quantification and explainability.

Transients: and what they tell us about the Universe

  • The environments of supernovae, and what they tell us about massive star evolution
  • Observation and characterisation of transients in the optical.

Thomas Killestein

PhD student University of Warwick