Yuki Atsusaka

WELCOME! I am a Ph.D. (political science) and M.A. (statistics) Candidate at Rice University (contact: atsusaka[at]rice.edu). Thank you for visiting my website.

I study American Politics and Political Methodology. Substantively, I study how electoral engineering affects racial minority representation in the U.S. Methodologically, I develop statistical and mathematical tools for studying racial and ethnic politics, minority representation, and electoral engineering (including redistricting and changing electoral systems). My current works study how rank data analysis (as part of computational social science) and quantitatively predictive logical models can advance political science research and legal debates about minority representation. My dissertation develops new methods to study the effects of ranked-choice voting on minority representation.

My Curriculum Vitae is available here. I am on Twitter too.


2. Atsusaka, Yuki and Randolph T. Stevenson. 2021. A Bias-Corrected Estimator for the Crosswise Model with Inattentive Respondents Forthcoming at Political Analysis [R Package: cWise] [Article Summary] [Replication Files]

1. Atsusaka, Yuki. 2021. A Logical Model for Predicting Minority Representation: Application to Redistricting and Voting Rights Cases American Political Science Review (Publisher’s Version: First View) [R Package: logical] [Article Summary] [Replication Files]

Working Papers

Note: The following is sorted by the type of methodology. All papers address questions in racial and ethnic politics and minority representation.

Quantitatively Predictive Logical Models
“A Logical Model Approach to Racially Polarized Voting, Descriptive Representation, and Electoral Engineering” (To be presented at PolMeth and in “Issues in Redistricting” panel at APSA)
“Reconsidering the Effect of At-Large Elections on Minority Representation” (with Iris E. Acquarone)

Rank Data Analysis
Does Ranked-Choice Voting Reduce Racial Polarization? (with Theo Landsman) [Media Coverage] (Dissertation Paper)
A winner of New America’s Electoral Reform Research Group Grant
“Statistical Methods for Partially Ranked Ballot Data” (Dissertation Paper)
“An Ecological Inference Model with Rank Data for Social Sciences” (with Thomas Weighill)
“Ranked Preferences over National Policy, Pork Barrel, and Casework by Race” (with Matthew Hayes)
“A Framework for Rank Data Analysis in Political Science”

Causal Inference/Program Evaluation
“Causal Inference with Rankings as Generalized Discrete Outcomes” (Dissertation Paper)
“A Machine Learning Method for Post-Stratification of Heterogeneous Treatment Effects” (with Raymond Duch)
A Unified Theory of the Effect of Vote-by-Mail on Turnout (with Robert M. Stein)

Survey Methodology
“Diagnostic Tools for the Crosswise Model: Synthesizing Application and Validation Studies”


In my dissertation, I develop statistical methods for analyzing rank data. Substantively, my project examines the consequences of an emerging electoral reform — switching from first-past-the-post to ranked-choice voting — for minority representation in the U.S. My dissertation is supported by the Electoral Reform Research Group (New America) and is composed of following papers:

“Does Ranked-Choice Voting Reduce Racially Polarized Voting?” (with Theo Landsman)
“Statistical Methods for Partially Ranked Ballot Data”
“Causal Inference with Rankings as Generalized Discrete Outcomes”

More information is available here.


  1. cWise: A (Cross)Wise Method to Analyze Sensitive Survey Questions
  2. logical: Computing and Visualizing Quantitative Predictions of Logical Models


As an instructor, I have taught the Math Prep (aka Math Prefresher) for the first-year graduate students in 2018-2019, Social Analysis and Simulation in R for the second-year graduate students in 2019, and Ecological Inference in Advanced Political Methodology in 2019. In addition, I have worked as a teaching assistant for Causal Inference (Michelle Torres, Fall 2019), Advanced Maximum Likelihood Estimation (Randy Stevenson, Spring 2019), and Machine Learning/Computational Social Science (Michelle Torres, Fall 2020). I have also founded and organized the Rice Methodology Research Group in the Department of Political Science.


I am a Fulbright scholar from 2016 to 2021. I also hold an M.A. in American Studies with a focus on African American History and Culture.

I will be presenting my works at APSA on September, 2021. Looking forward to seeing you there!