HEATHER CHAMPION

I am a PhD candidate in philosophy of science. My research focuses on how machine learning (ML) impacts scientific discovery. I explore concepts of novelty and robustness relevant to scientific inferences with ML. Please see my academic website for more information: https://liminal-learner.github.io/champion/.

My interest in computational epistemology stems from my M.Sc. in medical physics, where I contributed to the development of an evolutionary optimization algorithm for radiotherapy treatment planning. I also developed computational models of several astrophysical phenomena throughout my B.Sc. in physics and astronomy. My professional experience as a data analyst and software developer further drives me to reflect on the epistemology of data mining and machine learning. I have gained practical and theoretical knowledge of artificial intelligence by participating in the Alberta Machine Intelligence Institute (Amii) / Canadian Institute for Advanced Research (CIFAR) Deep Learning Reinforcement Learning Summer School 2019.