Urban Research Corps Members
Meet members of the Institute’s Urban Research Corps. The URC is a research incubator that produces relevant insights about the fundamental processes driving urban change and develops tools to help build more sustainable, equitable, and connected cities. URC participants develop, test and deploy computational methods and design scalable tools to accelerate the practice of sustainable urban development at the local and global scales.
Eric Chandler is a graduate student in the Computational Analysis and Public Policy program at the University of Chicago’s Harris School of Public Policy. He is enthusiastic about complex systems, networks, and simulation as tools for understanding emergent social phenomena. Prior to graduate school, he has worked a variety of roles in software development and quality assurance, specializing in agent-based modeling and non-linear optimization methods. Eric holds a B.S. in Physics from Carnegie Mellon University.
Brenda Li is a graduate student in the Computational Analysis and Public Policy program at the University of Chicago’s Harris School of Public Policy. Prior to UChicago, Brenda worked as a research programmer at Mathematica in their Human Services division. There, she contributed her data analysis and technical skills to program evaluation and improvement projects in various policy fields that included education, early childhood, nutrition, and employment. Brenda holds a Bachelor of Arts in Mathematics from Middlebury College.
Caitlin is a graduate student in the Computational Analysis and Public Policy (CAPP) program at the Harris School of Public Policy, focusing on applying current data science techniques to solve social problems. Over the past summer, she worked on the Mansueto Institute’s Adaptive Control COVID-19 tracking project as a research assistant. Prior to moving to Chicago, Caitlin worked as a Data Scientist for Springer Nature, helping them to begin to develop their data science capabilities. Caitlin holds a B.S in psychology from University College London, and an M.S in behavioral genetics from King’s College London.
Merritt Smith is a graduate student in the Computational Analysis and Public Policy program at the University of Chicago’s Harris School of Public Policy. His background is in applying data science methods to public policy problems, primarily wealth inequality and bribery. Before coming to Chicago, he built models of bribery at TRACE International, culminating in a chapter in the book Corrosive. As a Research Engineer at the Mansueto Institute, he works on creating open-source tools and data infrastructure to understand cities. Merritt holds a Bachelor of Arts in Data Science and Public Policy from Tufts University.