Senior Lecturer in Astrophysics
My research focuses on the evolution of galaxies with the environment, encompassing both cluster galaxy evolution and the reasons for the peak in star formation rate seen at cosmic noon. I plan to use LSST to study the evolution of galaxies within clusters out to z=1.5 and beyond, with the kind of representative evolution-matched cluster mass samples that only LSST can provide.
I have also recently been using novel machine learning and computer vision techniques to detect galaxy clusters in preparation for LSST. We have performed a successful proof of concept with SDSS. The plan is also to use this method to confirm clusters within the LSST footprint selected by other methods, such as X-ray, SZ, and red sequence detection. These clusters will be characterized using machine learning to obtain their redshifts and richnesses etc. Again, we have a proof of concept with SDSS, which extracts accurate photo-z for cluster galaxies. We are currently testing out both our galaxy evolution research and cluster-finding techniques on the Subaru HSC survey data and potentially DP0.
I am a member of the Galaxies SC, DESC, and the LSST: UK Executive Board.