Nathan Jo is a Research Fellow (Computational Science) with the RegLab. He earned a BA in Applied Mathematics, a BA in Data Science, and an MS in Applied Data Science from the University of Southern California (USC) in 2021, where he graduated summa cum laude. During his time at USC, he worked on optimal decision making problems as a researcher at the Center for Artificial Intelligence in Society (CAIS) as well as powersharing, peace, and security problems at the Security and Political Economy Lab (SPEC). His research interests include causal inference, algorithmic fairness, and mechanism design, particularly as they apply to high-impact social problems.
Outside of research, Nathanael is passionate about service. He has worked as both a teaching volunteer in the Los Angeles Unified School District and also as a public advocacy intern for a United Nations nonprofit.