Postdoctoral Fellow, Astronomy
Department of Astronomy
Mario Juric, Astronomy
PhD, Physics & Astronomy, McMaster University, 2017
MSc, Physics, Engineering Physics, & Astronomy, Queen’s University, 2013
BSc, Physics, Minor in Publishing, Simon Fraser University, 2010
Gwendolyn Eadie’s research falls in the category of astrostatistics, an interdisciplinary field of astronomy and statistics. On the astronomy side, she is interested in properties of the Milky Way Galaxy such as its mass and amount of dark matter, as well as its stellar populations, globular cluster population, and central nuclear star cluster.
On the statistics side, she is interested in Bayesian hierarchical modeling, Markov chain Monte Carlo techniques, and in general, implementing and developing modern statistical methods to and for astronomical problems.
Eadie’s research confronts physical models with observational data through hierarchical Bayesian methods. Observational data in astronomy is undergoing a big data revolution. All-sky survey programs such as Gaia and the Large Synoptic Survey Telescope (LSST) are providing and will continue to offer vast amounts of data about the Milky Way Galaxy.
At the eScience Institute, Eadie is interested in harnessing these data sets with the best statistical tools in order to test physical models of the Milky Way. She hopes to learn not only about the Milky Way’s present properties and structure but also its formation history in the context of the larger Local Group of galaxies.