Connor Stone, PhD candidate, Astrophysics, supervised by Professor Stephane Courteau

Topic: The Galaxy Manifold: A statistical and systematic analysis of intrinsic galaxy properties. Overview:  I am exploring a multi-dimensional approach to galaxy modeling. Most traditional analysis is performed on correlations of two parameters at a time. I am developing a framework for examining trends in any number of parameters simultaneously. I use machine learning models and techniques to fully extract all available information. By determining which parameters are fundamentally linked to each other, I can connect models of galaxy formation to real observations and possibly learn about the nature of dark matter. Listen to Fast Radio Bursts on podcast, bring exciting space news hot off the telescope into your ears.