Rachel Newton is a PhD candidate in the Electrical and Computer Engineering department at the University of Michigan. She is broadly interested in ways to bridge the gap between theoretical machine learning and practical applications in different areas of electrical engineering. Her current research uses machine learning to improve the mathematical models used for control of large-scale systems such as wind farms, aircraft, and wireless communication networks. Outside of the lab, she enjoys west coast swing dancing, snowboarding, kayaking, and video games.