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Keir is a cosmologist with a strong interest in statistical and machine learning methods necessary for robust data analysis. He is particularly interested in testing the nature of the dark matter (e.g., ultra-light axions) using the large-scale structure (Lyman-alpha forest) and the cosmic microwave background (CMB). To enable this, he developed and applied a method for “emulating” (probabilistic interpolation of) hydrodynamical simulations using Bayesian optimisation. This technique can benefit cosmological studies using the large-scale structure and wherever simulations are prohibitively computationally-expensive. During his PhD at University College London (2018), he worked on removing Galactic contamination to allow a clear view of the primordial CMB; and built a simulation-calibrated model for the effect of high-density absorbers in the Lyman-alpha forest.
You can find out more about Keir’s research and outreach activities and contact him on his personal webpage: https://keirkwame.github.io .
