Supervisor for student research projects:

  • 2018/19: Proposal and supervision of an undergraduate summer research project at the Royal Observatory, Edinburgh. The project extends and merges different types of generative adversarial networks to create high-quality synthetic galaxy images for the calibration of shape measurement algorithms in weak lensing and dataset augmentation for deep learning approaches to galaxy classification and deblending. The resulting paper is published in MNRAS, Vol. 485(3), pp. 3203-3214.

TA at the School of Physics and Astronomy:

  • 2018/2019: Programming, Data Analysis and Machine Learning 2 (PGPH11102)
  • 2018/2019: Programming, Data Analysis and Machine Learning 1 (PGPH11102)
  • 2017/2018: Introductory Astrophysics (PHYS08050)

Guest lecturer for the Programming Society:

  • 2017/18: Introduction to Machine Learning, covering the implementation of naive Bayes classifiers
  • 2017/18: Building Probabilistic Simulations, covering Bayes’ theorem and the Monty Hall problem