Megan (she/her) is a student at the University of Chicago pursuing an M.S. in Computational Analysis and Public Policy. She received a B.Sc. in Computer Science from New York University Abu Dhabi where she conducted her thesis on network detection of censorship devices. After graduating from NYUAD, Megan worked as a software engineer at the Institute for Health Metrics and Evaluation in Seattle where she primarily worked on data engineering projects and optimizing health models. She then worked as a senior software engineer at a consulting company in Stockholm where she worked with a range of companies to improve and develop their data processes. Megan’s research interests are focused on using computational methods to better understand effective policy methods for inequality reduction, particularly in the areas of urban policy and tax policy.