Scott de Marchi

Scott de Marchi is a Professor of Political Science and Director of the Decision Science program at Duke University's Trinity College of Arts & Sciences. His research focuses on mathematical methods, including bargaining theory, computational social science, game theory, and machine learning, applied to decision-making in legislative contexts like the U.S. Congress and coalition negotiations. He has been funded by the Department of Defense, National Science Foundation, and USAID. His work bridges theoretical frameworks with empirical analysis, emphasizing interdisciplinary collaboration and methodological innovation.

Key research themes include legislative polarization, policy formation, and the computational modeling of political processes. Notable contributions address government formation mechanisms, roll-call voting patterns, and the application of agent-based models to simulate complex political dynamics. He advocates for rigorous documentation practices in research and has co-authored influential handbooks on political science methodologies.

• Grants: Department of Defense, NSF, USAID
• Labs/Teams: Leads Duke's Decision Science program, fostering computational social science initiatives

Publications span over two decades, emphasizing both theoretical advancements and practical applications in political decision-making. His work often integrates quantitative methods with qualitative insights to address real-world governance challenges.