معرفی
Yuki Shiraito is an Assistant Professor of Political Science at the University of Michigan, with affiliations to the Center for Political Studies (CPS), Center for Japanese Studies (CJS), and the Michigan Institute for Data Science (MIDAS). He holds a PhD in Politics from Princeton University (2017) and previously served as a postdoctoral fellow at Dartmouth College’s Program of Quantitative Social Science. His research focuses on political methodology, particularly Bayesian statistical models and large-scale computational algorithms for data analysis, with applications to international relations and comparative politics.
Shiraito’s scholarly work addresses topics such as autocratic legitimacy, public opinion on immigration and international law, and the methodological challenges in text classification and conjoint analysis. His contributions span academic journals including the American Political Science Review, Political Analysis, and European Political Science Review. He has also developed open-source software for improving text classification efficiency (e.g., the R package activeText). His educational background includes an LLM and LLB from the University of Tokyo, reflecting interdisciplinary training in law and political science.
Shiraito’s research and teaching emphasize the intersection of computational methods with substantive political questions, particularly in contexts involving Japan and other East Asian democracies. His current projects explore topics such as gendered policy preferences and the role of international organizations in shaping domestic policy support.
