Erin Hayes

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 SNIa in order to more precisely constrain cosmological constants. More broadly, I am interested in transient astronomy, dark matter and dark energy, large scale surveys, and machine learning in astronomy.

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 Rubin LSST and Roman Space Telescope.

Outside of research, I spend most of my time dancing, whether that be with the Cambridge University Ballet Club or with the Darwin College Cuban Salsa Group. You may also find me reading, hiking, or traveling whenever I get the opportunity.