My name is Erin Hayes and I am a Gates-Cambridge Scholar studying for my PhD at the University of Cambridge’s Institute of Astronomy (IoA). At the IoA, I work with Kaisey Mandel in the field of supernova cosmology. Specifically, I use BayeSN, a heirarchical Bayesian SED model, to better understand the properties of SN Ia in order to more precisely constrain cosmological constants. More broadly, I am interested in transient astronomy, dark matter and dark energy, strong lensing, large scale surveys, and astrostatistics.
Prior to arriving in Cambridge, I earned my BA and MS in Physics at the University of Pennsylvania. While there, I worked with Masao Sako to search for microlensing events in data from the Dark Energy Survey (DES) and to develop a machine learning method for classifying transients and variable objects in data from the Photometric LSST Astronomical Time-domain Classification Challenge (PLAsTiCC) in anticipation of the upcoming surge in data from the Vera C. Rubin Observatory's Legacy Survey of Space and Time (Rubin-LSST) and the Nancy Grace Roman Space Telescope.
Outside of research, I spend most of my time dancing, whether that be with the Cambridge University Dance Competition Team or with the Darwin College Cuban Salsa Group. You may also find me playing football, reading, hiking, or traveling whenever I get the opportunity.
White Cliffs of Dover, October 2022
York City Walls, April 2023
The Peak District, September 2023