Yuki Shiraito
Assistant Professor at University of Michigan
Ann Arbor, Michigan, United States
Summary
👤
Senior🎓
Top SchoolYuki Shiraito is an assistant professor at the University of Michigan with nine years of experience applying Bayesian modeling, statistical text analysis, and survey experiments to political methodology and applied statistics. Trained at Princeton (PhD) and The University of Tokyo (LLM, LLB), Yuki blends rigorous theoretical grounding with hands-on quantitative methods for social science research. Previously a postdoctoral researcher at Dartmouth’s Program in Quantitative Social Science, they specialize in methods that turn complex textual and survey data into causal and predictive insights. Based in Ann Arbor, Yuki is known for bridging advanced statistical modeling with practical applications in political science, often translating methodological innovations into reproducible research tools. An interdisciplinary scholar, they bring a legal and political foundation to computational approaches, enabling nuanced interpretation of empirical findings.
9 years of coding experience
1 year of employment as a software developer
University of TokyoDoctor of Philosophy - PhD, Political Science and Government, Doctor of Philosophy - PhD, Political Science and Government at Princeton University
Github Skills (9)
tf-idf6
graph4
lda4
phonetics4
r-package4
spark3
survey3
r2
text-classification2
Programming languages (3)
Github contributions (5)
shiraito/ScaBillMatch
Feb 2018 - Jul 2022
Policy diffusion in the US legislature
Contributions:11 pushes, 2 branches in 4 years 6 months
policydiffusionlegislature
SensitiveQuestions/endorse
Nov 2018 - May 2022
R endorse package for analyzing survey endorsement experiments
Contributions:3 commits, 3 PRs, 15 pushes in 3 years 6 months
analyzingsurveyendorsementrstats
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