Our Team

Erik Wibbels

Principal Investigator

Bio

Dr. Wibbels’ research focuses on development, decentralized governance, and other areas of political economy. He has worked with USAID’s DRG Centre, USAID mission officers, AidData, RTI International, the World Bank and others on projects around the world. Erik is the PI on the Machine Learning for Peace project.

Jeremy Springman

Director of Civic Research

Bio

Jeremy is a Senior Research Associate at DevLab@Duke and the Department of Political Science. He studies political economy in developing countries, with a specific interest in how non-profit organizations shape, and are shaped by, politics and governance. His work has received support from the National Science Foundation and the US Agency for International Development, among others.

Zung-Ru Lin

Data Scientist

Bio

Zung-Ru is working as a Data Scientist that helps solve technical issues encountered. His work mainly focuses on optimizing the overall functionality and productivity within the peace project pipeline framework and implementing NLP and various supervised machine learning methods in detecting civic-space changes.

Hanling Su

Data Scientist

Bio

Hanling is a Data Scientist with a specialization in data collection and preparation. Her work revolves around applying machine learning and natural language processing techniques to ensure data integrity for the Machine Learning for Peace project at DevLab. She also contributes to designing and monitoring the dashboard for the scraping process, offering the team clear visualizations of the project’s progress.

Rethis Togbedji Gansey

Predoctoral Research Coordinator

Bio

Rethis Togbedji Gansey is a Predoctoral Research Coordinator at DevLab@Penn and PDRI. His primary focus lies in the areas of Violence/conflict analysis, as well as Migration and Education in developing countries. He is also interested in the application of causal inference and impact evaluation methods to assess the effectiveness of public policies.

Jitender Swami

Predoctoral Research Coordinator

Bio

Donald Moratz

Research Associate

Bio

Donald Moratz is a Research Manager at the DevLab@Duke and the Department of Political Science at Duke University. His work focuses on the Machine Learning for Peace project and the integration of advanced numerical methods in political science. His substantive areas of interest are in the political economy of development as well as endogenous growth.

Mateo Villamizar Chaparro

PhD Candidate 

Bio

Mateo is a PhD student in political economy at the department of Political Science. His research interests include analyzing the politics of public goods’ distribution and violence in developing countries. With an emphasis in economic development, migration, state capacity and political institutions.

Serkant Adiguzel

Faculty Affiliate

Bio

Serkant is a Ph.D. candidate at the Department of Political Science at Duke University and a Middle East Initiative predoctoral fellow at the Harvard Kennedy School. He specializes in political economy and political methodology. His research interests lie at the intersection of the political economy of democratic backsliding, digital media, and public services.

Diego Romero

Faculty Affiliate

Bio

Diego is a PhD candidate at Duke University’s Political Science Department specializing in Political Economy and Political Methodology. He is interested in issues of governance, in particular corruption and accountability. His other research interests include reintegration of deported migrants and the spatial distribution of public service delivery.

Arda Enfiyeci

Undergraduate Research Fellow

Bio

Andreas Beger

Consultant

Bio

Andreas Beger is an independent consultant with 10 years experience in developing data-driven geopolitical forecasting systems. He has worked on projects funded by the Intelligence Advanced Research Projects Activity (IARPA), the Political Instability Task Force (PITF), the Varieties of Democracy (V-Dem) Institute, and others. He received a Ph.D. in political science from Florida State University in 2012.

This project would not have been possible without the key contributions of Scott de Marchi and Spencer Dorsey. We thank Tim McDade, Akanksha Bhattacharyya, Clara Suong, and Joan Timoneda for their earlier work on MLP. We thank Sanjit Beriwal, Mitali Mishra, Jonathan Sandoval, Nikhil Srivastava, Mike Sun, and Huong Vu for their excellent research assistance.