Kosuke Imai's Curriculum Vitae

 

  Contact Information

1737 Cambridge Street
Institute for Quantitative Social Science
Harvard University
Cambridge, MA 02138
Phone: 617-384-6778
Email: Imai at Harvard dot Edu
URL: https://imai.fas.harvard.edu

  Education

Ph.D. in Political Science, Harvard University (1999 - 2003).
A.M. in Statistics, Harvard University (2000 - 2002).
B.A. in Liberal Arts, The University of Tokyo (1994 - 1998).

  Positions

Professor, Department of Government and Department of Statistics, Harvard University (2018 - present)
Professor, Department of Politics and Center for Statistics and Machine Learning, Princeton University (2013 - 2018)
    Founding Director, Program in Statistics and Machine Learning (2013 - 2017)
Professor of Visiting Status, Graduate Schools of Law and Politics, The University of Tokyo (2016 - 2023)
Associate Professor, Department of Politics, Princeton University (2012 - 2013)
Assistant Professor, Department of Politics, Princeton University (2004 - 2012)
Visiting Researcher, Faculty of Economics, The University of Tokyo (August, 2006)
Instructor, Department of Politics, Princeton University (2003 - 2004)

  Honors and Awards

Graduate Student Association Faculty Mentorship Award for outstanding graduate student mentorship, awarded by the Graduate Student Association, Department of Government, Harvard University (2023).
Highly Cited Researcher for ``production of multiple highly cited papers that rank in the top 1% by citations for field and year in Web of Science,'' awarded by Clarivate Analytics (cross-field, 2018, 2019, 2020, 2021; social sciences, 2022, 2023).
Statistical Software Award for developing statistical software that makes a significant research contribution, for ``redist: Simulation Methods for Legislative Redistricting,'' awarded by the Society for Political Methodology (2022).
Honarable Mention, Best Conference Paper Award, for ``A Statistical Model of Bipartite Networks: Application to Cosponsorship in the United States Senate,'' awarded by Political Network Section, American Political Science Association (2022).
James Francis Hannan Lectureship. Department of Statistics and Probability, Michigan State University (declined; 2022).
Invited to read ``Experimental Evaluation of Computer-Assisted Human Decision-Making: Application to Pretrial Risk Assessment Instrument.'' before the Royal Statistical Society Research Section, London (2022).
Excellence in Mentoring Award, awarded by the Society for Political Methodology (2021).
Statistical Software Award for developing statistical software that makes a significant research contribution, for ``fastLink: Fast Probabilistic Record Linkage,'' awarded by the Society for Political Methodology (2021).
President, the Society of Political Methodology (2017-2019). Vice President and President-elect (2015-2017).
Elected Fellow, the Society of Political Methodology (2017).
The Nils Petter Gleditsch Article of the Year Award, awarded by Journal of Peace Research (2017).
Statistical Software Award for developing statistical software that makes a significant research contribution, for ``mediation: R Package for Causal Mediation Analysis,'' awarded by the Society for Political Methodology (2015).
Outstanding Reviewer Award for Journal of Educaional and Behavioral Statistics, given by the American Educational Research Association (2014).
The Stanley Kelley, Jr. Teaching Award, given by the Department of Politics, Princeton University (2013).
Pi Sigma Alpha Award for the best paper presented at the 2012 Midwest Political Science Association annual meeting, for ``Explaining Support for Combatants during Wartime: A Survey Experiment in Afghanistan,'' awarded by the Midwest Political Science Association (2013).
Invited to read ``Experimental Designs for Identifying Causal Mechanisms'' before the Royal Statistical Society Research Section, London (2012).
Inaugural recipient of the Emerging Scholar Award for a young scholar making exceptional contributions to political methodology who is within ten years of their terminal degree, awarded by the Society for Political Methodology (2011).
Political Analysis Editors' Choice Award for an article providing an especially significant contribution to political methodology, for ``Estimation of Heterogeneous Treatment Effects from Randomized Experiments, with Application to the Optimal Planning of the Get-out-the-vote Campaign,'' awarded by the Society for Political Methodology and Oxford University Press (2011).
The Tom Ten Have Memorial Award for the best poster presented at the 2011 Atlantic Causal Inference Conference, for ``Identifying Treatment Effect Heterogeneity through Optimal Classification and Variable Selection,'' awarded by the Departments of Biostatistics and Statistics, University of Michigan (2011).
Nominated for the Graduate Mentoring Award, The McGraw Center for Teaching and Learning, Princeton University (2010, 2011).
New Hot Paper, for the most-cited paper in the field of Economics & Business in the last two months among papers published in the last year, for ``Misunderstandings among Experimentalists and Observationalists about Causal Inference,'' named by Thomson Reuters' ScienceWatch (2009).
Warren Miller Prize for the best article published in Political Analysis, for ``Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference,'' awarded by the Society for Political Methodology and Oxford University Press (2008).
Fast Breaking Paper for the article with the largest percentage increase in citations among those in the top 1% of total citations across the social sciences in the last two years, for ``Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference,'' named by Thomson Reuters' ScienceWatch (2008).
Pharmacoepidemiology and Drug Safety Outstanding Reviewer Recognition (2008).
Miyake Award for the best political science article published in 2005, for ``Do Get-Out-The-Vote Calls Reduce Turnout? The Importance of Statistical Methods for Field Experiments,'' awarded by the Japanese Political Science Association (2006).
Toppan Prize for the best dissertation in political science, for Essays on Political Methodology, awarded by Harvard University (2004). Also, nominated for American Political Science Association E.E. Schattschneider Award for the best doctoral dissertation in the field of American government and politics.

  Selected Manuscripts

Ben-Michael, Eli, D. James Greiner, Melody Huang, Kosuke Imai, Zhichao Jiang, Sooahn Shin. ``Does AI help humans make better decisions? A methodological framework for experimental evaluation.''
Jia, Zeyang, Kosuke Imai, and Michael Lingzhi Li. ``The Cram Method for Efficient Simultaneous Learning and Evaluation.''
Johnson, Rebecca A., Tyler Simko, and Kosuke Imai. ``A Summer Bridge Program for First-Generation Low-Income Students Stretches Academic Ambitions with No Adverse Impacts on GPA.''
Chattopadhyay, Ambarish, Kosuke Imai, and Jose R. Zubizarreta. ``Design-based inference for generalized network experiments with stochastic interventions.''
Zhang, Yi and Kosuke Imai. ``Individualized Policy Evaluation and Learning under Clustered Network Interference.''
Li, Michael Lingzhi and Kosuke Imai. ``Statistical Performance Guarantee for Subgroup Identification with Generic Machine Learning.''
Jia, Zeyang, Eli Ben-Michael, and Kosuke Imai. ``Bayesian Safe Policy Learning with Chance Constrained Optimization: Application to Military Security Assessment during the Vietnam War.''
Kenny, Christopher, Shiro Kuriwaki, Cory McCartan, Tyler Simko, and Kosuke Imai. ``Evaluating Bias and Noise Induced by the U.S. Census Bureau's Privacy Protection Methods.''
Blackwell, Matthew, Jacob R. Brown, Sophie Hill, Kosuke Imai, and Teppei Yamamoto. ``Priming bias versus post-treatment bias in experimental designs..''
McCartan, Cory, Tyler Simko, and Kosuke Imai. ``Making Differential Privacy Work for Census Data Users.''
Lo, Adeline, Santiago Olivella, and Kosuke Imai. ``A Statistical Model of Bipartite Networks: Application to Cosponsorship in the United States Senate..''
McCartan, Cory, Jacob Goldin, Daniel E. Ho, Kosuke Imai. Estimating Racial Disparities When Race is Not Observed.''
Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li. ``Distributionally Robust Causal Inference with Observational Data.''
Zhang, Yi, Eli Ben-Michael, and Kosuke Imai. ``Safe Policy Learning under Regression Discontinuity Designs.''
Imai, Kosuke and Michael Lingzhi Li. ``Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments.''
Goplerud, Max, Kosuke Imai, Nicole E. Pashley. ``Estimating Heterogeneous Causal Effects of High-Dimensional Treatments: Application to Conjoint Analysis.''
Malani, Anup, Phoebe Holtzman, Kosuke Imai, Cynthia Kinnan, Morgen Miller, Shailender Swaminathan, Alessandra Voena, Bartosz Woda, and Gabriella Conti. ``Effect of Health Insurance in India: A Randomized Controlled Trial.''
Ben-Michael, Eli, D. James Greiner, Kosuke Imai, and Zhichao Jiang. ``Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment.''
Tarr, Alexander and Kosuke Imai. ``Estimating Average Treatment Effects with Support Vector Machines.''
Chan, K.C.G, K. Imai, S.C.P. Yam, Z. Zhang. ``Efficient Nonparametric Estimation of Causal Mediation Effects.''
Barber, Michael and Kosuke Imai. ``Estimating Neighborhood Effects on Turnout from Geocoded Voter Registration Records.''
Hirano, Shigeo, Kosuke Imai, Yuki Shiraito, and Masaki Taniguchi. ``Policy Positions in Mixed Member Electoral Systems: Evidence from Japan.''

  Publications in English

     Books

Llaudet, Elena, and Kosuke Imai. (2022). Data Analysis for Social Science: A Friendly and Practical Introduction. Princeton University Press.
Imai, Kosuke. (2017). Quantitative Social Science: An Introduction. Princeton University Press. Translated into Japanese (2018), Chinese (2020), and Korean (2021).
    Stata version (2021) with Lori D. Bougher.
    Tidyverse version (2022) with Nora Webb Williams.

     Refereed Journal Articles

McCartan, Cory, Jacob Brown, and Kosuke Imai. ``Measuring and Modeling Neighborhoods.'' American Political Science Review, Forthcoming.
Ben-Michael, Eli, Kosuke Imai, and Zhichao Jiang. ``Policy Learning with Asymmetric Counterfactual Utilities.'' Journal of the American Statistical Association, Forthcoming.
Ham, Dae Woong, Kosuke Imai, and Lucas Janson. ``Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis.'' Political Analysis, Forthcoming.
Eshima, Shusei, Kosuke Imai, and Tomoya Sasaki. ``Keyword Assisted Topic Models.'' American Journal of Political Science, Forthcoming.
Kenny, Christopher, Cory McCartan, Tyler Simko, and Kosuke Imai. (2024). ``Census officials must constructively engage with independent evaluations.'' Proceedings of the National Academy of Sciences (Letter), Vol. 121, No. 11, e2321196121.
McCartan, Cory and Kosuke Imai. (2023). ``Sequential Monte Carlo for Sampling Balanced and Compact Redistricting Plans.'' Annals of Applied Statistics, Vol. 17, No. 4 (December), pp. 3300-3323.
Tarr, Alexander, June Hwang, and Kosuke Imai. (2023). ``Automated Coding of Political Campaign Advertisement Videos: An Empirical Validation Study.'' Political Analysis, Vol. 31, No. 4 (October), pp. 554-574.
Jiang, Zhichao, Kosuke Imai, and Anup Malani. (2023). ``Statistical Inference and Power Analysis for Direct and Spillover Effects in Two-Stage Randomized Experiments.'' Biometrics, Vol. 79, No. 3 (September), pp. 2370-2381.
Imai, Kosuke, In Song Kim, and Erik Wang. (2023). ``Matching Methods for Causal Inference with Time-Series Cross-Sectional Data.'' American Journal of Political Science, Vol. 67, No. 3 (July), pp. 587-605.
Kenny, Christopher T., Cory McCartan, Tyler Simko, Shiro Kuriwaki, and Kosuke Imai. (2023). ``Widespread Partisan Gerrymandering Mostly Cancels Nationally, but Reduces Electoral Competition.'' Proceedings of the National Academy of Sciences, Vol. 120, No. 25, e2217322120.
Imai, Kosuke and Zhichao Jiang. (2023). ``Principal Fairness for Human and Algorithmic Decision-Making.'' Statistical Science, Vol. 38, No. 2 (July), pp317-328.
McCartan, Cory, Tyler Simko, and Kosuke Imai. (2023). ``Researchers need better access to US Census data.'' Science, Vol. 380, No. 6648 pp. 902-903.
Imai, Kosuke, Zhichao Jiang, D. James Greiner, Ryan Halen, and Sooahn Shin. (2023). ``Experimental Evaluation of Algorithm-Assisted Human Decision-Making: Application to Pretrial Public Safety Assessment.'' (with discussion) Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 186, No. 2 (April), pp. 167-189. Read before the Royal Statistical Society.
Rosenman, Evan T.R., Santiago Olivella, and Kosuke Imai. (2023). ``Race and ethnicity data for first, middle, and last names.'' Scientific Data, Vol. 10, No. 299, pp. 1-11.
Imai, Kosuke and Michael Lingzhi Li. (2023). ``Experimental Evaluation of Individualized Treatment Rules.'' Journal of the American Statistical Association, Vol. 118, No. 541, pp. 242-256.
Kenny, Christopher T., Shiro Kuriwaki, Cory McCartan, Evan T.R. Rosenman, Tyler Simko, and Kosuke Imai. (2023). ``Comment: The Essential Role of Policy Evaluation for the 2020 Census Disclosure Avoidance System..'' Harvard Data Science Review, Special Issue 2: Dierential Privacy for the 2020 U.S. Census (January), pp. 1-16.
Fan, Jianqing, Kosuke Imai, Inbeom Lee, Han Liu, Yang Ning, and Xiaolin Yang. (2023). ``Optimal Covariate Balancing Conditions in Propensity Score Estimation.'' Journal of Business & Economic Statistics, Vol. 41, No. 1, pp. 97-110.
Imai, Kosuke, Santiago Olivella, and Evan T.R. Rosenman. (2022). ``Addressing Census data problems in race imputation via fully Bayesian Improved Surname Geocoding and name supplements.'' Science Advances, Vol. 8, No. 49, pp. 1-10.
Papadogeorgou, Georgia, Kosuke Imai, Jason Lyall, and Fan Li. (2022). ``Causal Inference with Spatio-temporal Data: Estimating the Effects of Airstrikes on Insurgent Violence in Iraq.'' Journal of the Royal Statistical Society, Series B (Statistical Methodology), Vol. 84, No. 5 (November), pp. 1969-1999.
McCartan, Cory, Christopher T. Kenny, Tyler Simko, George Garcia III, Kevin Wang, Melissa Wu, Shiro Kuriwaki, and Kosuke Imai. (2022). ``Simulated redistricting plans for the analysis and evaluation of redistricting in the United States: 50stateSimulations.'' Scientific Data, Vol. 9, No. 689, pp. 1-10.
Olivella, Santiago, Tyler Pratt, and Kosuke Imai. (2022). ``Dynamic Stochastic Blockmodel Regression for Network Data: Application to International Conflicts.'' Journal of the American Statistical Association, Vol. 117, No. 539, pp. 1068-1081.
de la Cuesta, Brandon, Naoki Egami, and Kosuke Imai. (2022). ``Improving the External Validity of Conjoint Analysis: The Essential Role of Profile Distribution.'' Political Analysis, Vol. 30, No. 1 (January), pp. 19-45.
Kenny, Christopher T., Shiro Kuriwaki, Cory McCartan, Evan Rosenman, Tyler Simko, and Kosuke Imai. (2021). ``The Use of Differential Privacy for Census Data and its Impact on Redistricting: The Case of the 2020 U.S. Census.'' Science Advances, Vol. 7, No. 7 (October), pp. 1-17.
Imai, Kosuke and James Lo. (2021). ``Robustness of Empirical Evidence for the Democratic Peace: A Nonparametric Sensitivity Analysis.'' International Organization, Vol. 75, No. 3 (Summer), pp. 901-919.
Imai, Kosuke, Zhichao Jiang, and Anup Malani. (2021). ``Causal Inference with Interference and Noncompliance in Two-Stage Randomized Experiments.'' Journal of the American Statistical Association, Vol. 116, No. 534, pp. 632-644.
Imai, Kosuke and In Song Kim. (2021). ``On the Use of Two-way Fixed Effects Regression Models for Causal Inference with Panel Data.'' Political Analysis, Vol. 29, No. 3 (July), pp. 405-415.
Imai, Kosuke, and Zhichao Jiang. (2020). ``Identification and Sensitivity Analysis of Contagion Effects in Randomized Placebo-Controlled Trials.'' Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 183, No. 4 (October), pp. 1637-1657.
Fifield, Benjamin, Michael Higgins, Kosuke Imai, and Alex Tarr. (2020). ``Automated Redistricting Simulation Using Markov Chain Monte Carlo.'' Journal of Computational and Graphical Statistics, Vol. 29, No. 4, pp. 715-728.
Fifield, Benjamin, Kosuke Imai, Jun Kawahara, and Christopher T. Kenny. (2020). ``The Essential Role of Empirical Validation in Legislative Redistricting Simulation.'' Statistics and Public Policy, Vol. 7, No. 1, pp 52-68.
Ning, Yang, Sida Peng, and Kosuke Imai. (2020). ``Robust Estimation of Causal Effects via High-Dimensional Covariate Balancing Propensity Score..'' Biometrika, Vol. 107, No. 3 (September), pp. 533-554.
Chou, Winston, Kosuke Imai, and Bryn Rosenfeld. (2020). ``Sensitive Survey Questions with Auxiliary Information.'' Sociological Methods & Research, Vol. 49, No. 2 (May), pp. 418-454.
Imai, Kosuke, Gary King, and Carlos Velasco Rivera. (2020). ``Do Nonpartisan Programmatic Policies Have Partisan Electoral Effects? Evidence from Two Large Scale Randomized Experiments.'' Journal of Politics, Vol. 82, No. 2 (April), pp. 714-730.
Zhao, Shandong, David A. van Dyk, and Kosuke Imai. (2020). ``Propensity-Score Based Methods for Causal Inference in Observational Studies with Non-Binary Treatments.'' Statistical Methods in Medical Research, Vol. 29, No. 3 (March), pp. 709-727.
Lyall, Jason, Yang-Yang Zhou, and Kosuke Imai. (2020). ``Can Economic Assistance Shape Combatant Support in Wartime? Experimental Evidence from Afghanistan.'' American Political Science Review, Vol. 114, No. 1 (February), pp. 126-143.
Kim, In Song, Steven Liao, and Kosuke Imai. (2020). ``Measuring Trade Profile with Granular Product-level Trade Data.'' American Journal of Political Science, Vol. 64, No. 1 (January), pp. 102-117.
Enamorado, Ted, and Kosuke Imai. (2019). ``Validating Self-reported Turnout by Linking Public Opinion Surveys with Administrative Records.'' Public Opinion Quarterly, Vol. 83, No. 4 (Winter), pp. 723-748.
Blair, Graeme, Winston Chou, and Kosuke Imai. (2019). ``List Experiments with Measurement Error.'' Political Analysis, Vol. 27, No. 4 (October), pp. 455-480.
Egami, Naoki, and Kosuke Imai. (2019). ``Causal Interaction in Factorial Experiments: Application to Conjoint Analysis.'' Journal of the American Statistical Association, Vol. 114, No. 526 (June), pp. 529-540.
Enamorado, Ted, Benjamin Fifield, and Kosuke Imai. (2019). ``Using a Probabilistic Model to Assist Merging of Large-scale Administrative Records.'' American Political Science Review, Vol. 113, No. 2 (May), pp. 353-371.
Imai, Kosuke and In Song Kim. (2019). ``When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data?'' American Journal of Political Science, Vol. 63, No. 2 (April), pp. 467-490.
Imai, Kosuke, and Zhichao Jiang. (2018). ``A Sensitivity Analysis for Missing Outcomes Due to Truncation-by-Death under the Matched-Pairs Design.'' Statistics in Medicine, Vol. 37, No. 20 (September), pp. 2907-2922.
Fong, Christian, Chad Hazlett, and Kosuke Imai. (2018). ``Covariate Balancing Propensity Score for a Continuous Treatment: Application to the Efficacy of Political Advertisements.'' Annals of Applied Statistics, Vol. 12, No. 1, pp. 156-177.
Benjamin, Daniel J., et al. (2018). ``Redefine Statistical Significance.'' Nature Human Behaviour. Vol. 2, No. 1, pp. 6-10.
Hirose, Kentaro, Kosuke Imai, and Jason Lyall. (2017). ``Can Civilian Attitudes Predict Insurgent Violence?: Ideology and Insurgent Tactical Choice in Civil War.'' Journal of Peace Research, Vol. 51, No. 1 (January), pp. 47-63. Winner of the Nils Petter Gleditsch Article of the Year Award. Story by Princeton's communication office.
Imai, Kosuke, James Lo, and Jonathan Olmsted. (2016). ``Fast Estimation of Ideal Points with Massive Data.'' American Political Science Review, Vol. 110, No. 4 (December), pp. 631-656.
Rosenfeld, Bryn, Kosuke Imai, and Jacob Shapiro. (2016). ``An Empirical Validation Study of Popular Survey Methodologies for Sensitive Questions.'' American Journal of Political Science, Vol. 60, No. 3 (July), pp. 783-802.
Imai, Kosuke and Kabir Khanna. (2016). ``Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Record.'' Political Analysis, Vol. 24, No. 2 (Spring), pp. 263-272.
Blair, Graeme, Kosuke Imai, and Yang-Yang Zhou. (2015). ``Design and Analysis of the Randomized Response Technique.'' Journal of the American Statistical Association, Vol. 110, No. 511 (September), pp. 1304-1319.
Imai, Kosuke and Marc Ratkovic. (2015). ``Robust Estimation of Inverse Probability Weights for Marginal Structural Models.'' Journal of the American Statistical Association, Vol. 110, No. 511 (September), pp. 1013-1023.
Lyall, Jason, Yuki Shiraito, and Kosuke Imai. (2015). ``Coethnic Bias and Wartime Informing.'' Journal of Politics, Vol. 77, No. 3 (July), p. 833-848.
Imai, Kosuke, Bethany Park, and Kenneth Greene. (2015). ``Using the Predicted Responses from List Experiments as Explanatory Variables in Regression Models.'' Political Analysis, Vol. 23, No. 2 (Spring), pp. 180-196. Translated in Portuguese and Reprinted in Revista Debates Vol. 9, No 1.
Blair, Graeme, Kosuke Imai, and Jason Lyall. (2014). ``Comparing and Combining List and Endorsement Experiments: Evidence from Afghanistan.'' American Journal of Political Science, Vol. 58, No. 4 (October), pp. 1043-1063.
Tingley, Dustin, Teppei Yamamoto, Kentaro Hirose, Luke Keele, and Kosuke Imai. (2014). ``mediation: R Package for Causal Mediation Analysis.'' Journal of Statistical Software, Vol. 59, No. 5 (August), pp. 1-38.
Imai, Kosuke and Marc Ratkovic. (2014). ``Covariate Balancing Propensity Score.'' Journal of the Royal Statistical Society, Series B (Statistical Methodology), Vol. 76, No. 1 (January), pp. 243-263.
Lyall, Jason, Graeme Blair, and Kosuke Imai. (2013). ``Explaining Support for Combatants during Wartime: A Survey Experiment in Afghanistan.'' American Political Science Review, Vol. 107, No. 4 (November), pp. 679-705. Winner of the Pi Sigma Alpha Award.
Imai, Kosuke and Teppei Yamamoto. (2013). ``Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments.'' Political Analysis, Vol. 21, No. 2 (Spring), pp. 141-171. (lead article)
Imai, Kosuke and Marc Ratkovic. (2013). ``Estimating Treatment Effect Heterogeneity in Randomized Program Evaluation.'' Annals of Applied Statistics, Vol. 7, No. 1 (March), pp. 443-470. Winner of the Tom Ten Have Memorial Award. Reprinted in Advances in Political Methodology, R. Franzese, Jr. ed., Edward Elger, 2017.
Imai, Kosuke, Dustin Tingley, and Teppei Yamamoto. (2013). ``Experimental Designs for Identifying Causal Mechanisms.'' (with discussions) Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 176, No. 1 (January), pp. 5-51. (lead article) Read before the Royal Statistical Society in March 2012.
Imai, Kosuke, and Dustin Tingley. (2012). ``A Statistical Method for Empirical Testing of Competing Theories.'' American Journal of Political Science, Vol. 56, No. 1 (January), pp. 218-236.
Blair, Graeme and Kosuke Imai. (2012). ``Statistical Analysis of List Experiments.'' Political Analysis, Vol. 20, No. 1 (Winter), pp. 47-77.
Imai, Kosuke, Luke Keele, Dustin Tingley, and Teppei Yamamoto. (2011). ``Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies.'' American Political Science Review, Vol. 105, No. 4 (November), pp. 765-789. Reprinted in Advances in Political Methodology, R. Franzese, Jr. ed., Edward Elger, 2017.
Bullock, Will, Kosuke Imai, and Jacob Shapiro. (2011). ``Statistical Analysis of Endorsement Experiments: Measuring Support for Militant Groups in Pakistan.'' Political Analysis, Vol. 19, No. 4 (Autumn), pp. 363-384. (lead article)
Imai, Kosuke. (2011). ``Multivariate Regression Analysis for the Item Count Technique.'' Journal of the American Statistical Association, Vol. 106, No. 494 (June), pp. 407-416. (featured article)
Ho, Daniel E., Kosuke Imai, Gary King, and Elizabeth Stuart. (2011). ``MatchIt: Nonparametric Preprocessing for Parametric Causal Inference.'' Journal of Statistical Software, Vol. 42 (Special Volume on Political Methodology), No. 8 (June), pp. 1-28.
Imai, Kosuke, Ying Lu, and Aaron Strauss. (2011). ``eco: R Package for Ecological Inference in 2 x 2 Tables.'' Journal of Statistical Software, Vol. 42 (Special Volume on Political Methodology), No. 5 (June), pp. 1-23.
Imai, Kosuke, and Aaron Strauss. (2011). ``Estimation of Heterogeneous Treatment Effects from Randomized Experiments, with Application to the Optimal Planning of the Get-out-the-vote Campaign.'' Political Analysis, Vol. 19, No. 1 (Winter), pp. 1-19. (lead article). Winner of the Political Analysis Editors' Choice Award.
Imai, Kosuke, Luke Keele, and Dustin Tingley. (2010). ``A General Approach to Causal Mediation Analysis.'' Psychological Methods, Vol. 15, No. 4 (December), pp. 309-334. (lead article).
Imai, Kosuke, and Teppei Yamamoto. (2010). ``Causal Inference with Differential Measurement Error: Nonparametric Identification and Sensitivity Analysis.'' American Journal of Political Science, Vol. 54, No. 2 (April), pp. 543-560.
Imai, Kosuke, Luke Keele, and Teppei Yamamoto. (2010). ``Identification, Inference, and Sensitivity Analysis for Causal Mediation Effects.'' Statistical Science, Vol. 25, No. 1 (February), pp. 51-71.
King, Gary, Emmanuela Gakidou, Kosuke Imai, Jason Lakin, Ryan T. Moore, Clayton Nall, Nirmala Ravishankar, Manett Vargas, Martha María Téllez-Rojo, Juan Eugenio Hernández Ávila, Mauricio Hernández Ávila, and Héctor Hernández Llamas. (2009). ``Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme,'' (with a comment) The Lancet, Vol. 373, No. 9673 (April), pp. 1447-1454.
Imai, Kosuke, Gary King, and Clayton Nall. (2009). ``The Essential Role of Pair Matching in Cluster-Randomized Experiments, with Application to the Mexican Universal Health Insurance Evaluation.'' (with discussions and rejoinder) Statistical Science, Vol. 24, No. 1 (February), pp. 29-53.
Imai, Kosuke. (2009). ``Statistical Analysis of Randomized Experiments with Nonignorable Binary Missing Outcomes: An Application to a Voting Experiment.'' Journal of the Royal Statistical Society, Series C (Applied Statistics), Vol. 58, No. 1 (February), pp. 83-104.
Imai, Kosuke, Gary King, and Olivia Lau. (2008).``Toward A Common Framework of Statistical Analysis and Development.'' Journal of Computational and Graphical Statistics, Vol. 17, No. 4 (December), pp. 892-913.
Imai, Kosuke. (2008). ``Variance Identification and Efficiency Analysis in Randomized Experiments under the Matched-Pair Design.'' Statistics in Medicine, Vol. 27, No. 24 (October), pp. 4857-4873.
Ho, Daniel E., and Kosuke Imai. (2008). ``Estimating Causal Effects of Ballot Order from a Randomized Natural Experiment: California Alphabet Lottery, 1978-2002.'' Public Opinion Quarterly, Vol. 72, No. 2 (Summer), pp. 216-240.
Imai, Kosuke, Gary King, and Elizabeth A. Stuart. (2008). ``Misunderstandings among Experimentalists and Observationalists about Causal Inference.'' Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 171, No. 2 (April), pp. 481-502. Reprinted in Field Experiments and their Critics, D. Teele ed. (2014), New Haven: Yale University Press.
Imai, Kosuke, Ying Lu, and Aaron Strauss. (2008). ``Bayesian and Likelihood Inference for 2 x 2 Ecological Tables: An Incomplete Data Approach.'' Political Analysis, Vol. 16, No. 1 (Winter), pp. 41-69.
Imai, Kosuke. (2008). ``Sharp Bounds on the Causal Effects in Randomized Experiments with ``Truncation-by-Death''.'' Statistics & Probability Letters, Vol. 78, No. 2 (February), pp. 144-149.
Imai, Kosuke, and Samir Soneji. (2007). ``On the Estimation of Disability-Free Life Expectancy: Sullivan's Method and Its Extension.'' Journal of the American Statistical Association, Vol. 102, No. 480 (December), pp. 1199-1211.
Horiuchi, Yusaku, Kosuke Imai, and Naoko Taniguchi. (2007). ``Designing and Analyzing Randomized Experiments: Application to a Japanese Election Survey Experiment.'' American Journal of Political Science, Vol. 51, No. 3 (July), pp. 669-687.
Ho, Daniel E., Kosuke Imai, Gary King, and Elizabeth A. Stuart. (2007). ``Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference.'' Political Analysis, Vol. 15, No. 3 (Summer), pp. 199-236. (lead article). Winner of the Warren Miller Prize.
Ho, Daniel E., and Kosuke Imai. (2006). ``Randomization Inference With Natural Experiments: An Analysis of Ballot Effects in the 2003 California Recall Election.'' Journal of the American Statistical Association, Vol. 101, No. 475 (September), pp. 888-900.
Imai, Kosuke, and David A. van Dyk. (2005). ``MNP: R Package for Fitting the Multinomial Probit Model.'' Journal of Statistical Software, Vol. 14, No. 3 (May), pp. 1-32. abstract reprinted in Journal of Computational and Graphical Statistics, (2005) Vol. 14, No. 3 (September), p. 747
Imai, Kosuke. (2005). ``Do Get-Out-The-Vote Calls Reduce Turnout? The Importance of Statistical Methods for Field Experiments,'' American Political Science Review, Vol. 99, No. 2 (May), pp. 283-300.
Imai, Kosuke, and David A. van Dyk. (2005). ``A Bayesian Analysis of the Multinomial Probit Model Using Marginal Data Augmentation,'' Journal of Econometrics, Vol. 124, No. 2 (February), pp. 311-334.
Imai, Kosuke, and David A. van Dyk. (2004). ``Causal Inference With General Treatment Regimes: Generalizing the Propensity Score,'' Journal of the American Statistical Association, Vol. 99, No. 467 (September), pp. 854-866.
Imai, Kosuke, and Gary King. (2004). ``Did Illegal Overseas Absentee Ballots Decide the 2000 U.S. Presidential Election?'' Perspectives on Politics, Vol. 2, No. 3 (September), pp. 537-549. Our analysis is a part of The New York Times article, ``How Bush Took Florida: Mining the Overseas Absentee Vote'' By David Barstow and Don van Natta Jr. July 15, 2001, Page 1, Column 1.

     Refereed Conference Proceedings

Svyatkovskiy, Alexey, Kosuke Imai, Mary Kroeger, and Yuki Shiraito. (2016). ``Large-scale text processing pipeline with Apache Spark.'' IEEE International Conference on Big Data, Washington, DC, pp. 3928-3935.

     Invited Contributions

Imai, Kosuke, Michael Rosenblum, and Mark Rothmann. (2023). ``14th Annual University of Pennsylvania Conference on statistical issues in clinical trials/subgroup analysis in clinical trials: Opportunities and challenges (afternoon panel discussion).'' Clinical Trials, Vol. 24, No. 4, pp. 405-415.
Imai, Kosuke, Zhichao Jiang, D. James Greiner, Ryan Halen, and Sooahn Shin. (2023). ``Authors' Reply to the Discussion of `Experimental Evaluation of Algorithm-Assisted Human Decision-Making: Application to Pretrial Public Safety Assessment.''' Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 186, No. 2 (April), pp. 212–216.
Imai, Kosuke, and Yang Ning. (2023). ``Covariate Balancing Propensity Score.'' Handbook of Matching and Weighting Adjustments for Causal Inference. Zubizarreta, Jose R., Elizabeth A. Stuart, Dylan S. Small, and Paul R. Rosenbaum (eds). Chapman & Hall. pp. 283-292.
Imai, Kosuke. (2022). ``Causal Diagrams and Social Science Research.'' Probabilistic and Causal Inference: The Works of Judea Pearl. Geffner, Hector and Dechter, Rina and Halpern, Joseph Y. (eds). Association for Computing Machinery and Morgan & Claypool, pp. 647-654.
Imai, Kosuke, and Zhichao Jiang. (2019). ``Comment: The Challenges of Multiple Causes.'' Journal of the American Statistical Association, Vol. 114, No. 528, pp. 1605-1610.
de la Cuesta, Brandon and Kosuke Imai. (2016). ``Misunderstandings about the Regression Discontinuity Design in the Study of Close Elections.'' Annual Review of Political Science, Vol. 19, pp. 375-396.
Imai, Kosuke. (2016). ``Book Review of Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. by Guido W. Imbens and Donald B. Rubin.'' Journal of the American Statistical Association, Vol. 111, No. 515, pp. 1365-1366.
Imai, Kosuke, Bethany Park, and Kenneth F. Greene. (2015). ``Usando as respostas previsiveis da abordagem list-experiments como variáveis explicativas em modelos de regressao.'' Revista Debates, Vol. 9, No. 1, pp. 121-151. First printed in Political Analysis, Vol. 23, No. 2 (Spring).
Imai, Kosuke, Luke Keele, Dustin Tingley, and Teppei Yamamoto. (2014). ``Comment on Pearl: Practical Implications of Theoretical Results for Causal Mediation Analysis.'' Psychological Methods, Vol. 19, No. 4 (December), pp. 482-487.
Imai, Kosuke, Gary King, and Elizabeth A. Stuart. (2014). ``Misunderstandings among Experimentalists and Observationalists about Causal Inference.'' in Field Experiments and their Critics: Essays on the Uses and Abuses of Experimentation in the Social Sciences, D. Teele ed., New Haven: Yale University Press, pp. 196-227. First printed in Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 171, No. 2 (April).
Imai, Kosuke, Dustin Tingley, and Teppei Yamamoto. (2013). ``Reply to Discussions of ``Experimental Designs for Identifying Causal Mechanisms.'' Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 176, No. 1 (January), pp. 46-49.
Imai, Kosuke. (2012). ``Comments: Improving Weighting Methods for Causal Mediation Analysis.'' Journal of Research on Educational Effectiveness, Vol. 5, No. 3, pp. 293-295.
Imai, Kosuke. (2011). ``Introduction to the Virtual Issue: Past and Future Research Agenda on Causal Inference.'' Political Analysis, Virtual Issue: Causal Inference and Political Methodology.
Imai, Kosuke, Booil Jo, and Elizabeth A. Stuart. (2011). ``Commentary: Using Potential Outcomes to Understand Causal Mediation Analysis.'' Multivariate Behavioral Research, Vol. 46, No. 5, pp. 842-854.
Imai, Kosuke, Luke Keele, Dustin Tingley, and Teppei Yamamoto. (2010). ``Causal Mediation Analysis Using R,'' in Advances in Social Science Research Using R, H. D. Vinod ed., New York: Springer (Lecture Notes in Statistics), pp. 129-154.
Imai, Kosuke, Gary King, and Clayton Nall. (2009). ``Rejoinder: Matched Pairs and the Future of Cluster-Randomized Experiments.'' Statistical Science, Vol. 24, No. 1 (February), pp. 65-72.
Imai, Kosuke. (2003) ``Review of Jeff Gill's Bayesian Methods: A Social and Behavioral Sciences Approach,'' The Political Methodologist, Vol. 11, No. 1, pp. 9-10.

     Other Publications

Goldstein, Daniel, Kosuke Imai, Anja S. Goritz, and Peter M. Gollwitzer. (2008). ``Nudging Turnout: Mere Measurement and Implementation Planning of Intentions to Vote.''
Ho, Daniel E. and Kosuke Imai. (2004). ``The Impact of Partisan Electoral Regulation: Ballot Effects from the California Alphabet Lottery, 1978-2002,'' Princeton Law & Public Affairs Paper No. 04-001: Harvard Public Law Working Paper No. 89.
Imai, Kosuke. (2003) ``Essays on Political Methodology,'' Ph.D. Thesis, Department of Government, Harvard University.
Imai, Kosuke, and Jeremy Weinstein. (2000) ``Measuring the Economic Impact of Civil War,'' Harvard University Center for International Development, Working Paper Series, No. 51.

  Publications in Japanese

Imai, Kosuke. (2022). ``Ippyo no Kakusa: Algorithm de Kaizen Dekiru.'' Nikkei Business, December 19, pp.72-75.
Imai, Kosuke. (2007). ``Keiryo Seijigaku niokeru Ingateki Suiron (Causal Inference in Quantitative Political Science).'' Leviathan, Vol. 40, pp. 224-233.
Horiuchi, Yusaku, Kosuke Imai, and Naoko Taniguchi. (2005). ``Seisaku Jyoho to Tohyo Sanka: Field Jikken ni yoru Kensyo (Policy Information and Voter Participation: A Field Experiment).'' Nenpo Seijigaku (The Annals of the Japanese Political Science Association), 2005-I, pp. 161-180.
Taniguchi, Naoko, Yusaku Horiuchi, and Kosuke Imai. (2004). ``Seito Saito no Etsuran ha Tohyo Kodo ni Eikyo Suruka? (Does Visiting Political Pary Websites Influence Voting Behavior?).'' Nikkei Research Report, Vol. IV, pp. 16-19.

  Statistical Software

Mukaigawara, Mitsuru, Georgia Papadogeorgou, Jason Lyall, and Kosuke Imai. ``geocausal: Causal Inference with Spatio-Temporal Data.'' available through The Comprehensive R Archive Network and GitHub.
Shin, Sooahn, Zhichao Jiang, and Kosuke Imai. ``aihuman: Experimental Evaluation of Algorithm-Assisted Human Decision-Making .'' available through The Comprehensive R Archive Network and GitHub.
Huang, Karissa, Zhichao Jiang, and Kosuke Imai. ``RCT2: Designing and Analyzing Two-Stage Randomized Experiments.'' available through The Comprehensive R Archive Network and GitHub.
Christopher T. Kenny, Cory McCartan, Benjamin Fifield, and Kosuke Imai. ``redistmetrics: Redistricting Metrics.'' available through The Comprehensive R Archive Network and GitHub.
Eshima, Shusei, Kosuke Imai, and Tomoya Sasaki. ``keyATM: Keyword Assisted Topic Models.'' available through The Comprehensive R Archive Network and GitHub
Li, Michael Lingzhi and Kosuke Imai. ``evalITR: Evaluating Individualized Treatment Rules.'' available through The Comprehensive R Archive Network and GitHub
Egami, Naoki, Brandon de la Cuesta, and Kosuke Imai. ``factorEx: Design and Analysis for Factorial Experiments.'' available through The Comprehensive R Archive Network and GitHub
Kim, In Song, Erik Wang, Adam Rauh, and Kosuke Imai. ``PanelMatch: Matching Methods for Causal Inference with Time-Series Cross-Section Data.'' available through GitHub 2018.
Olivella, Santiago, Adeline Lo, Tyler Pratt, and Kosuke Imai. ``NetMix: Mixed-membership Regression Stochastic Blockmodel for Networks.'' available through CRAN and Github. 2019.
Egami, Naoki, Brandon de la Cuesta, and Kosuke Imai. ``factorEx: Design and Analysis for Factorial Experiments.'' available through The Comprehensive R Archive Network and GitHub. 2019.
Enamorado, Ted, Benjamin Fifield, and Kosuke Imai. ``fastLink: Fast Probabilistic Record Linkage.'' available through The Comprehensive R Archive Network and GitHub. Winner of the Statistical Software Award. 2017.
Khanna, Kabir, Brandon Bertelsen, Santiago Olivella, Evan Rosenman, and Kosuke Imai. ``wru: Who Are You? Bayesian Predictions of Racial Category Using Surname, First Name, Middle Name, and Geolocation.'' available through The Comprehensive R Archive Network and GitHub. 2015.
Christopher T. Kenny, Cory McCartan, Benjamin Fifield, and Kosuke Imai. ``redist: Computational Algorithms for Redistricting Simulation.'' available through The Comprehensive R Archive Network and GitHub. Winner of the Statistical Software Award. 2022.
Imai, Kosuke, James Lo, and Jonathan Olmsted. ``emIRT: EM Algorithms for Estimating Item Response Theory Models.'' available through The Comprehensive R Archive Network and the GitHub. 2015.
Blair, Graeme, Yang-Yang Zhou, and Kosuke Imai. ``rr: Statistical Methods for the Randomized Response Technique.'' available through The Comprehensive R Archive Network and GitHub. 2015.
Fong, Christian, Marc Ratkovic, Chad Hazlett, and Kosuke Imai. ``CBPS: R Package for Covariate Balancing Propensity Score.'' available through The Comprehensive R Archive Network. 2012-2014.
Egami, Naoki, Marc Ratkovic, and Kosuke Imai. ``FintIt: R Package for Finding Heterogeneous Treatment Effects.'' available through The Comprehensive R Archive Network. 2012-2015.
Kim, In Song and Kosuke Imai. ``wfe: Weighted Linear Fixed Effects Regression Models for Causal Infernece.'' available through The Comprehensive R Archive Network. 2011-2012.
Shiraito, Yuki, and Kosuke Imai. ``endorse: R Package for Analyzing Endorsement Experiments.'' available through The Comprehensive R Archive Network and GitHub. 2012-2014.
Blair, Graeme, and Kosuke Imai. ``list: Statistical Methods for the Item Count Technique and List Experiment..'' available through The Comprehensive R Archive Network and GitHub. 2011-2014.
Tingley, Dustin, Teppei Yamamoto, Kentaro Hirose, Luke Keele, and Kosuke Imai. ``mediation: R Package for Causal Mediation Analysis.'' available through The Comprehensive R Archive Network. 2009-2014. Winner of the Statistical Software Award. Reviewed in Journal of Educational and Behavioral Statistics
Imai, Kosuke. ``experiment: R Package for Designing and Analyzing Randomized Experiments.'' available through The Comprehensive R Archive Network. 2007.
Ho, Daniel E., Kosuke Imai, Gary King, and Elizabeth Stuart. ``MatchIt: Nonparametric Preprocessing for Parametric Causal Inference.'' available through The Comprehensive R Archive Network. 2005-2013.
Imai, Kosuke, Ying Lu, and Aaron Strauss. ``eco: Ecological Inference in 2 x 2 Tables.'' available through The Comprehensive R Archive Network. 2004-2015.
Imai, Kosuke, and David A. van Dyk. ``MNP: R Package for Fitting the Multinomial Probit Model.'' available through The Comprehensive R Archive Network and GitHub. 2004-2013.
Imai, Kosuke, Gary King, and Olivia Lau. ``Zelig: Everyone's Statistical Software.'' available through The Comprehensive R Archive Network. 2004-2013.

  External Research Grants

     Principal and Co-Principal Investigator

National Institute of Mental Health (2022-2027). ``The impact of social drivers, conditional cash transfers and their mechanisms on mental health of the young: an integrated retrospective and forecasting approach using the 100 million Brazilian Cohort.'' (1R01MH128911-01) Co-Principal Investigator (with Daiane Borges Machado et al.). $1,993,614.
National Science Foundation (2022-2025). ``Collaborative Research: Understanding the Evolution of Political Campaign Advertisements over the Last Century.'' (Accountable Institutions and Behavior Program, SES-2148928). Principal Investigator (with Michael Crespin and Bryce Dietrich) $538,484.
Meta Research Grant (2022). $50,000.
National Science Foundation (2021-2023). ``Collaborative Research: Causal Inference with Spatio-Temporal Data on Human Dynamics in Conflict Settings.'' (Algorithm for Threat Detection Program; DMS-2124463). Principal Investigator (with Georgia Papadogeorgou and Jason Lyall) $485,340.
National Science Foundation (2021-2023). ``Evaluating the Impacts of Machine Learning Algorithms on Human Decisions.'' (Methodology, Measurement, and Statistics Program; SES-2051196). Principal Investigator (with D. James Greiner and Zhichao Jiang) $330,000.
Cisco Systems, Inc. (2020-2022). ``Evaluating the Impacts of Algorithmic Recommendations on the Fairness of Human Decisions.'' (Ethics in AI; CG# 2370386) Principal Investigator (with D. James Greiner and Zhichao Jiang) $110,085.
The Alfred P. Sloan Foundation (2020-2022). ``Causal Inference with Complex Treatment Regimes: Design, Identification, Estimation, and Heterogeneity.'' (Economics Program; 2020-13946) Co-Principal Investigator (with Francesca Dominici and Jose Zubizarreta) $996,299.
Facebook Research Grant (2018). $25,000.
National Science Foundation (2016-2021). ``Collaborative Conference Proposal: Support for Conferences and Mentoring of Women and Underrepresented Groups in Political Methodology.'' (Methodology, Measurement and Statistics and Political Science Programs; SES-1628102) Principal Investigator (with Jeffrey Lewis) $312,322. Supplement (SES-1831370) $60,000.
The United States Agency for International Development (2015-2017). ``Unemployment and Insurgent Violence in Afghanistan: Evidence from the Community Development Program.'' (AID-OAA-A-12-00096) Principal Investigator (with Jason Lyall) $188,037.
The United States Institute of Peace (2015-2016). ``Assessing the Links between Economic Interventions and Stability: An impact evaluation of vocational and skills training in Kandahar, Afghanistan,'' Principal Investigator (with David Haines, Jon Kurtz, and Jason Lyall) $144,494.
Amazon Web Services in Education Research Grant (2014). Principal Investigator (with Graeme Blair and Carlos Velasco Rivera) $3,000.
Development Bank of Latin America (CAF) (2013). ``The Origins of Citizen Support for Narcos: An Empirical Investigation,'' Principal Investigator (with Graeme Blair, Fabiana Machado, and Carlos Velasco). $15,000.
The International Growth Centre (2011-2013). ``Poverty, Militancy, and Citizen Demands in Natural Resource-Rich Regions: Randomized Evaluation of the Oil Profits Dividend Plan for the Niger Delta'' (RA-2010-12-013). Principal Investigator (with Graeme Blair). $117,116.
National Science Foundation, (2009-2012). ``Statistical Analysis of Causal Mechanisms: Identification, Inference, and Sensitivity Analysis,'' (Methodology, Measurement, and Statistics Program and Political Science Program; SES-0918968) Principal Investigator. $97,574.
National Science Foundation, (2009-2011). ``Collaborative Research: The Measurement and Identification of Media Priming Effects in Political Science,'' (Methodology, Measurement, and Statistics Program and Political Science Program; SES-0849715) Principal Investigator (with Nicholas Valentino). $317,126.
National Science Foundation, (2008-2009). ``New Statistical Methods for Randomized Experiments in Political Science and Public Policy,'' (Political Science Program; SES-0752050) Principal Investigator. $52,565.
National Science Foundation, (2006-2009). ``Collaborative Research: Generalized Propensity Score Methods,'' (Methodology, Measurement and Statistics Program; SES-0550873) Principal Investigator (with Donald B. Rubin and David A. van Dyk). $460,000.
The Telecommunications Advancement Foundation, (2004). ``Analyzing the Effects of Party Webpages on Political Opinions and Voting Behavior,'' Principal Investigator (with Naoko Taniguchi and Yusaku Horiuchi). $12,000.

     Adviser and Statistical Consultant

National Science Foundation (2016-2017). ``Doctoral Dissertation Research: Crossing Africa's Arbitrary Borders: How Refugees Shape National Boundaries by Challenging Them.'' (Political Science Program, SES-1560636). Principal Investigator and Adviser for Co-PI Yang-Yang Zhou's Dissertation Research. $18,900.
Institute of Education Sciences (2012-2014). ``Academic and Behavioral Consequences of Visible Security Measures in Schools'' (R305A120181). Statistical Consultant (Emily Tanner-Smith, Principal Investigator). $351,228.
National Science Foundation (2013-2014). ``Doctoral Dissertation Research: Open Trade for Sale: Lobbying by Productive Exporting Firm'' (Political Science Program, SES-1264090). Principal Investigator and Adviser for Co-PI In Song Kim's Dissertation Research. $22,540.
National Science Foundation (2012-2013). ``Doctoral Dissertation Research: The Politics of Location in Resource Rent Distribution and the Projection of Power in Africa'' (Political Science Program, SES-1260754). Principal Investigator and Adviser for Co-PI Graeme Blair's Dissertation Research. $17,640.

  Selected Presentations

Keynote speaker, Promises and Limits of Inferring Protected-Class Data for Disparate Impact Testing of AI Systems, DLA Piper and O'Neil Risk Consulting & Algorithmic Auditing, 2023.
Distinguished speaker, Hariri Institute for Computing and Computational Science and Engineering, Boston University, 2023.
Keynote speaker, Michigan Student Symposium for Interdisciplinary Statistical Sciences (MSSISS), 2023.
Keynote speaker, CIVICA Data Science Days, The European University of Social Sciences, 2022.
Distinguished speaker, Harvard College Summer Program for Undergraduates in Data Science, 2021.
Keynote speaker, Kansas-Western Missouri Chapter of the American Statistical Association, 2021.
Invited plenary panelist. Association for Computing Machinery Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2021.
Keynote speaker, Taiwan Political Science Association, 2020.
Keynote speaker, Boston Japanese Researchers Forum, Massachusetts Institute of Technology, 2020.
Keynote speaker, Causal Mediation Analysis Training, Mailman School of Public Health, Columbia University, 2020.
Keynote speaker, Special Workshop on Evidence-based Policy Making. World Economic Forum, Centre for the Fourth Industrial Revolution, Japan, 2020.
Distinguished speaker, Institute for Data, Systems, and Society. Massachusetts Institute of Technology, 2019.
Keynote speaker, The Harvard Experimental Political Science Graduate Student Conference, Harvard University, 2019.
Invited speaker, Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-based AI. Association for the Advancement of Artificial Intelligence, Spring Symposium, Stanford University, 2019.
Inaugural speaker, Causal Inference Seminar, Departments of Biostatistics and Statistics, Boston University, 2019.
Keynote speaker, The Second Latin American Political Methodology Meeting, Universidad de los Andes, 2018.
Keynote speaker, The First Latin American Political Methodology Meeting, Pontifical Catholic University of Chile, 2017.
Keynote speaker, Workshop on Causal Mechanisms, University of Munich (Department of Economics), 2016.
Keynote speaker, The National Quality Registry Research Conference, Stockholm, 2016.
Keynote speaker, The UK-Causal Inference Meeting, University of Bristol (School of Mathematics), 2015.
Keynote speaker, The UP-STAT Conference, the Upstate Chapters of the American Statistical Association, 2015.
Keynote speaker, The Winter Conference in Statistics, Swedish Statistical Society and Umea University (Department of Mathematics and Mathematical Statistics), 2015.
Inaugural invited speaker, The International Methodology Colloquium, Rice University, 2015.
Invited speaker, The International Meeting on Experimental and Behavioral Social Sciences, University of Oxford (Nuffield College), 2014.
Keynote speaker, The Annual Meeting of the Australian Society for Quantitative Political Science, University of Sydney, 2013.
Keynote speaker, The Graduate Student Conference on Experiments in Interactive Decision Making, Princeton University, 2008.

  Invited Short Courses and Outreach Lectures

Short Course on Causal Inference; Department of Political Science, Rice University, 2009; Institute of Political Science, Academia Sinica, 2014.
Short Course on Causal Inference and Identification, Empirical Implications of Theoretical Models (EITM) Summer Institute - Harris School of Public Policy, University of Chicago, 2011; Department of Politics, Princeton University, 2012.
Short Course on Covariate Balancing Propensity Score; Society for Research on Educational Effectiveness Conference, Washington DC, Spring 2013; Uppsala University, 2016
Short Course on Causal Mediation Analysis: Summer Graduate Seminar, Istitute of Statistical Mathematics, Tokyo Japan, 2010; Society for Research on Educational Effectiveness Conference, Washington DC, Fall 2011, Spring 2012, Spring 2015; Inter-American Development Bank, 2012; Center for Education Research, University of Wisconsin, Madison, 2012; Bobst Center for Peace and Justice, Princeton University, 2014; Graduate School of Education, University of Pennsylvania, 2014; EITM Summer Institute, Duke University, 2014; Center for Lifespan Psychology, Max Planck Institute for Human Development, 2015; School of Communication Research, University of Amsterdam, 2015; Uppsala University, 2016
Short Course on Matching Methods for Causal Inference; Institute of Behavioral Science, University of Colorado, Boulder, 2009; Duke University, 2013.
Lecture on Statistics and Social Sciences: New Jersey Japanese School, 2011, 2016; Kaisei High School, 2012, 2014; Princeton University (Wilson College), 2012; University of Tokyo, 2014

  Conferences Organized

The First Asian Political Methodology Meeting (January 2014; co-organizer)
The Experimental Research Workshop (September 2012; co-organizer)
The 12th World Meeting of the International Society for Bayesian Analysis (June 2012; a member of the organizing committee)
Conference on Causal Inference and the Study of Conflict and State Building (May 2012; organizer)
The 28th Annual Society for Political Methodology Summer Meeting (July 2011; host)
Conference on New Methodologies and their Applications in Comparative Politics and International Relations (February 2011; co-organizer)

  Teaching

     Courses Taught at Harvard

Stat 286/Gov 2003: Causal Inference (formally Stat 186/Gov 2002): introduction to causal inference
Gov 2017: Applied Bayesian Statistics for Social Sciences
Gov 2003: Topics in Quantitative Methdology: causal inference, applied Bayesian statistics, machine learning

     Courses Taught at Princeton

POL 245 Visualizing Data: Exploratory data analysis, Graphical statistics, Data visualization
POL 345 Quantitative Analysis and Politics: a first course in quantitative social science
POL 451 Statistical Methods in Political Science: basic probability and statistical theory, their applications in the social sciences.
POL 502 Mathematics for Political Science: real analysis, linear algebra, calculus.
POL 571 Quantitative Analysis I: probability theory, statistical theory, linear models.
POL 572 Quantitative Analysis II: intermediate applied statistics.
POL 573 Quantitative Analysis III: advanced applied statistics.
POL 574 Quantitative Analysis IV: advanced applied statistics with various topics including Bayesian statistis and causal inference.
Reading courses basic mathematical probability and statistics, applied Bayesian statistics, spatial statistics.

  Advising

     Current Students

Maria Ballesteros (Government)
Sima Biondi (Government)
Kyla Chasalow (Statistics)
Dae Woong Ham (Statistics). To be Assistant Professor, Technology and Operations, Michigan Ross Business School
Zeyang Jia (Statistics)
Christopher T. Kenny (Government)
Jialu Li (Government)
Taegyun Lim (Government)
Qi Liu (Government)
Ruofan Ma (Government)
Jerry Min (Government)
Mitsuru Mukaigawara (Government)
Kentaro Nakamura (Harvard Kennedy School)
Philip O'Sullivan (Statistics and Harvard Law School)
Sun Young Park (Government)
Averell Schmidt (Harvard Kennedy School)
Sooahn Shin (Government)
Tyler Simko (Government). To be Assistant Professor, Department of Political Science, University of Michigan
Souhardya Sengupta (Statistics)
Dom Valentino (Government)
Yi Zhang (Statistics)

     Current Predocs and Postdocs

Melody Huang. To be Assistant Professor, Department of Political Science and Depart- ment of Statistics and Data Science, Yale University

     Former Students

Adam Breuer (Ph.D. in 2023, Department of Computer Science and Department of Government). Assistant Professor, Department of Government and Department of Computer Science, Dartmouth College
Sayumi Miyano (Ph.D. in 2023, Department of Politics, Princeton University) Postdoctoral Fellow, US-Japan Program, Harvard University. Followed by Assistant Professor, The Osaka School of International Public Policy at Osaka University
Shusei Eshima (Ph.D. in 2023, Department of Government, Harvard University; Dissertation Committee Chair). Data Scientist, Netflix
Casey Petroff (Ph.D. in 2023, Harvard Kennedy School). Assistant Professor, Department of Political Science, University of Rochester
Soubhik Barari (Ph.D. in 2023, Department of Government, Harvard University). Research Methdoologist, NORC at the University of Chicago
Cory McCartan (Ph.D. in 2023, Department of Statistics; Dissertation Committee Chair). Postdoctoral Fellow, Center for Data Science, New York University, followed by Assitant Professor, Department of Statistics, Pennsylvania State University
Soichiro Yamauchi (Ph.D. in 2022, Department of Government, Harvard University; Dissertation Committee Chair). Data Scientist at Google
Georgina Evans (Ph.D. in 2022, Department of Government, Harvard University). Research Scientist, Google Brain
Ambarish Chattopadhyay (Ph.D. in 2022, Department of Statistics, Harvard University). Postdoctoral fellow, Stanford University
Jacob Brown (Ph.D. in 2022, Department of Government, Harvard University). Assistant Professor, Department of Political Science, Boston University
Michael Lingzhe Li (Ph.D. in 2021, Operations Research, MIT). Assistant Professor, Technology and Operations Management Unit, Harvard Business School
Alexander Tarr (Ph.D. in 2021, Department of Electrical and Computer Engineering, Princeton University; Dissertation Committee Chair)
Connor Jerzak (Ph.D. in 2021, Department of Government, Harvard University). Assistant Professor, Department of Government, University of Texas, Austin
Shiro Kuriwaki (Ph.D. in 2021, Department of Government, Harvard University). Assistant Professor, Department of Political Science, Yale University
Erik Wang (Ph.D. in 2020, Department of Politics, Princeton University). Assistant Professor, Department of Politics, New York University
Diana Stanescu (Ph.D. in 2020, Department of Politics, Princeton University). Postdoctoral Fellow, Stanford University
Nicole Pashley (Ph.D. in 2020, Department of Statistics, Harvard University). Assistant Professor, Department of Statistics, Rutgers University
Asya Magazinnik (Ph.D. in 2020, Department of Politics, Princeton University). Assistant Professor, Department of Political Science, Massachusetts Institute of Technology
Max Goplerud (Ph.D. in 2020, Department of Government, Harvard University). Assistant Professor, Department of Political Science, University of Pittsburgh
Naoki Egami (Ph.D. in 2020, Department of Politics, Princeton University; Dissertation Committee Chair). Assistant Professor, Department of Political Science, Columbia University
Brandon de la Cuesta. (Ph.D. in 2019, Department of Politics, Princeton University). Postdoctoral Fellow, Center on Global Poverty and Development, Stanford University
Yang-Yang Zhou. (Ph.D. in 2019, Department of Politics, Princeton University). Assistant Professor, Department of Political Science, University of British Columbia
Winston Chou. (Ph.D. in 2019, Department of Politics, Princeton University). Senior Data Scientist, Netflix
Ted Enamorado (Ph.D. in 2019, Department of Politics, Princeton University; Dissertation Committee Chair). Assistant Professor, Department of Political Science, Washington University in St. Louis
Benjamin Fifield (Ph.D. in 2018, Department of Politics, Princeton University; Dissertation Committee Chair). Data Scientist, Meta
Tyler Pratt (Ph.D. in 2018, Department of Politics, Princeton University). Assistant Professor, Department of Political Science, University of North Carolina at Chapel Hill
Romain Ferrali (Ph.D. in 2018, Department of Politics, Princeton University). Assistant Professor, Aix-Marseille School of Economics
Julia Morse (Ph.D. in 2017, Woodrow Wilson School, Princeton University). Assistant Professor, Department of Political Science, University of California, Santa Barbara
Yuki Shiraito (Ph.D. in 2017, Department of Politics, Princeton University; Dissertation Committee Chair). Assistant Professor, Department of Political Science, University of Michigan
Carlos Velasco Rivera (Ph.D. in 2016, Department of Politics, Princeton University). Research Scientist, Netflix
Gabriel Lopez Moctezuma (Ph.D. in 2016, Department of Politics, Princeton University). Assistant Professor, Division of the Humanities and Social Sciences, California Institute of Technology
Graeme Blair (Ph.D. in 2016, Department of Politics, Princeton University). Associate Professor, Department of Political Science, University of California, Los Angeles
Jaquilyn R Waddell Boie (Ph.D. in 2015, Department of Politics, Princeton University). Associate, Heidman Law Firm
Scott Abramson (Ph.D. in 2014, Department of Politics, Princeton University). Associate Professor, Department of Political Science, University of Rochester
Michael Barber (Ph.D. in 2014, Department of Politics, Princeton University). Associate Professor, Department of Political Science, Brigham Young University
In Song Kim (Ph.D. in 2014, Department of Politics, Princeton University). Associate Professor, Department of Political Science, Massachusetts Institute of Technology
Alex Ruder (Ph.D. in 2014, Department of Politics, Princeton University). CED Director and Principal Adviser, Federal Reserve Bank of Atlanta
Meredith Wilf (Ph.D. in 2014, Department of Politics, Princeton University). Senior Director, Capital Rx
Will Bullock (Ph.D. candidate, Department of Politics, Princeton University). Senior Researcher, Meta
Teppei Yamamoto (Ph.D. in 2011, Department of Politics, Princeton University; Dissertation Committee Chair). Professor, Department of Political Science, Massachusetts Institute of Technology
Dustin Tingley (Ph.D. in 2010, Department of Politics, Princeton University). Professor, Department of Government, Harvard University
Aaron Strauss (Ph.D. in 2009, Department of Politics, Princeton University). Former Executive Director, Analyst Institute
Samir Soneji (Ph.D. in 2008, Office of Population Research, Princeton University; Dissertation Committee Chair). Associate Professor, Department of Health Behavior at the Gillings School of Global Public Health, University of North Carolina, Chapel Hill
Ying Lu (Ph.D. in 2005, Woodrow Wilson School, Princeton University; Dissertation Committee Chair). Associate Professor, Steinhardt School of Culture, Education, and Human Development, New York University

     Former Predocs and Postdocs

Evan Rosenman. (Postdoctoral Fellow, 2021-2023) Assistant Professor, Department of Mathematical Sciences, Claremont McKenna College
Eli Ben-Michael (Postdoctoral Fellow, 2021 - 2022). Assistant Professor, Department of Statistics and Data Science and Heinz College of Informations Systems and Public Policy
Zhichao Jiang (Postdoctoral Fellow, 2016 - 2019). Professor, School of Mathematics, Sun Yat-sen University
Adeline Lo (Postdoctoral Fellow, 2016-2019). Assistant Professor, Department of Political Science, University of Wisconsin, Madison
Yunkyu Sohn (Postdoctoral Fellow, 2016-2018). Assistant Professor, Department of Sociology, Seoul National University
Xiaolin Yang (Postdoctoral Fellow, 2015-2017). Data Scientist, Amazon.
Santiago Olivella (Postdoctoral Fellow, 2015-2016). Associate Professor, Department of Political Science, The University of North Carolina at Chapel Hill
Derew Dimmery (Predoctoral Fellow, 2015-2016). Scientific Coordinator, University of Vienna
James Lo (Postdoctoral Fellow, 2014-2016). Data Scientist, Meta
Steven Liao (Predoctoral Fellow, 2014-2015). Assistant Professor, Department of Political Science, University of California, Riverside
Michael Higgins (Postdoctoral Fellow, 2013-2015). Associate Professor, Department of Statistics, Kansas State University
Kentaro Hirose (Postdoctoral Fellow, 2012-2015) Associate Professor, Faculty of International Studies and Regional Development, University of Niigata Prefecture
Chad Hazlett (Predoctoral Fellow, 2013-2014). Associate Professor, Departments of Political Science and Statistics, University of California, Los Angeles
Florian Hollenbach (Predoctoral Fellow, 2013-2014). Associate Professor, Department of International Economics, Government and Business at the Copenhagen Business School
Marc Ratkovic (Predoctoral and Postdoctoral Fellow, 2010-2012). Assistant Professor, Department of Politics, Princeton University.

  Editorial and Referee Service

Co-editor for Journal of Causal Inference (2014-present).
Associate editor for American Journal of Political Science (2014-2019), American Political Science Review (2022-present), Journal of Business & Economic Statistics (2015-2024), Journal of Causal Inference (2011-2014), Journal of Experimental Political Science (2013-2017), Observational Studies (2014-present), Political Analysis (2014-2017).
Editorial board member for Asian Journal of Comparative Politics (2014 - present), Journal of Educational and Behavioral Statistics (2011 - present), Journal of Politics (2007 - 2008, 2019-2020), Journal of Research on Educational Effectiveness (2014--2016), Political Analysis (2010 - 2013), Political Science Research and Methods (2019 - present).
Guest editor for Political Analysis virtual issue on causal inference (2011).
Referee for ACM Computing Surveys, American Economic Journal: Applied Economics, American Economic Review: Insights, American Journal of Evaluation, American Journal of Epidemiology, American Journal of Political Science, American Political Science Review, American Politics Research, American Sociological Review, Annals of Applied Statistics, Annals of Statistics, Annals of the Institute of Statistical Mathematics, Biometrics, Biometrika, Biostatistics, BMC Medical Research Methodology, British Journal of Mathematical and Statistical Psychology, British Journal of Political Science , Canadian Journal of Statistics, Chapman & Hall/CRC Press, Child Development, Communications for Statistical Applications and Methods, Computational Statistics and Data Analysis, Econometrica, Econometrics, Electoral Studies, Electronic Journal of Statistics, Empirical Economics, Environmental Management, Epidemiology, European Union Politics, IEEE Transactions on Information Theory, International Journal of Biostatistics, International Journal of Epidemiology International Journal of Public Opinion Research, International Migration Review, John Wiley & Sons, Journal of Applied Econometrics, Journal of Applied Statistics, Journal of Biopharmaceutical Statistics, Journal of Business and Economic Statistics, Journal of Causal Inference, Journal of Computational and Graphical Statistics, Journal of Conflict Resolution, Journal of Consulting and Clinical Psychology, Journal of Econometrics, Journal of Educational and Behavioral Statistics, Journal of Empirical Legal Studies, Journal of Multivariate Analysis, Journal of Official Statistics, Journal of Peace Research, Journal of Politics, Journal of Research on Educational Effectiveness, Journal of Statistical Planning and Inference, Journal of Statistical Software, Journal of Survey Statistics and Methodology, Journal of the American Statistical Association (Case Studies and Applications; Theory and Methods), Journal of the Japanese and International Economies, Journal of the Japan Statistical Society, Journal of the Royal Statistical Society (Series A; Series B; Series C), Law & Social Inquiry, Legislative Studies Quarterly, Management Science, Multivariate Behavioral Research, National Science Foundation (Economics; Methodology, Measurement, Statistics; Political Science), Natural Sciences and Engineering Research Council of Canada, Nature Machine Intelligence, NeuroImage, Osteoporosis International, Oxford Bulletin of Economics and Statistics, Pharmaceutical Statistics, Pharmacoepidemiology and Drug Safety, PLOS One, Policy and Internet, Political Analysis, Political Behavior, Political Communication, Political Research Quarterly, Political Science Research and Methods, Population Health Metrics, Population Studies, Prevention Science, Princeton University Press, Proceedings of the National Academy of Sciences, Psychological Methods, Psychometrika, Public Opinion Quarterly, Quarterly Journal of Economics, Quarterly Journal of Political Science, Review of Economics and Statistics, Routledge, Sage Publications, Scandinavian Journal of Statistics, Science, Sloan Foundation, Springer, Sociological Methodology, Statistical Methodology, Statistical Methods and Applications, Statistical Methods in Medical Research, Statistical Science, Statistica Sinica, Sociological Methods & Research, Statistics & Probability Letters, Statistics in Medicine, Systems Biology, U.S.-Israel Binational Science Foundation, Value in Health, World Politics.

  University and Departmental Committees

   Harvard University, Department of Government

Chair, Full Professor Promotion Committee (2023-2024)
Chair, Senior Faculty Search Committee (2022-2023)
Chair, Second-year Progress Committee (2023-2024)
Member, Chair's Advisory Committee (2023-2024)
Member, Senior Lecturer Search Committee (2022-2023)
Member, Curriculum and Educational Policy Committee (2020-2021, 2022-2023)
Member, Second Year Progress Committee (2019-2020)
Member, Graduate Placement Committee (2019-2020)
Member, Graduate Admissions Committee (2018-2019)
Member, Graduate Poster Session Committee (2018-2019)

   Harvard University, Department of Statistics

Member, Associate Professor Promotion Review Committee (2022-2023)
Chair, Senior Faculty Search Committee (2021-2022)
Member, Junior Faculty Search Committee (2018-2019)
Member, Second Year Progress Committee (2018-2019, 2020-2021)

   Harvard University, Other departments

Member, Senior Faculty Search Committee, Department of Economics (2022-2023)
Co-chair, Postdoctoral Fellow Selection Committee, Harvard Data Science Initiative (2022-2023)

   Princeton University

Executive Committee Member, Program in Statistics and Machine Learning (2013-2018)
Executive Committee Member, Committee for Statistical Studies (2011-2018)
Member, Organizing Committee, Retreat on Data and Information Science at Princeton (2016)
Member, Council of the Princeton University Community (2015)
Member, Search Committee for the Dean of College (2015)
Member, Committee on the Library and Computing (2013-2016)
Member, Committee on the Fund for Experimental Social Science (2013-2018)
Member, Personally Identifiable Research Data Group (2012-2018)
Member, Research Computing Advisory Group (2013-2018)
Member, Task Force on Statistics and Machine Learning (2014-2015)

  Princeton University, Department of Politics

Chair, Department Research and Computing Committee (2012-2018)
Chair, Formal and Quantitative Methods Junior Search Committee (2012-2013, 2014-2015, 2016-2017)
Chair, Reappointment Committee (2015-2016)
Member, Diversity Initiative Committee (2014-2015)
Member, American Politics Junior Search Committee (2012-2014)
Member, Department Chair's Advisery Committee (2010-2013, 2015-2016)
Member, Department Priority Committee (2012-2013, 2014-2015, 2016-2017)
Member, Formal and Quantitative Methods Curriculum Committee (2005-2006)
Member, Formal and Quantitative Methods Junior Search Committee (2009-2010, 2015-2016)
Member, Formal and Quantitative Methods Postdoc Search Committee (2009-current)
Member, Graduate Admissions Committee (2012-2013)
Member, Reappointment Committee (2014-2016)
Member, Space Committee (2014-2016)
Member, Undergraduate Curriculum Committee (2014-2015)
Member, Undergraduate Exam Committee (2007-2008)
Member, Undergraduate Thesis Prize Committee (2005-2006, 2008-2011)

  Princeton University, Center for Statistics and Machine Learning

Executive Committee Member (2016-2018)
Member, Search Committee (2015-2017)

  Services to the Profession

     National Academy of Sciences, Engineering, and Medicine

Committee on National Statistics, Division of Behavioral and Social Sciences and Education, Panel on the Review and Evaluation of the 2014 Survey of Income and Program Participation Content and Design (2014--2017)

     National Science Foundation

Proposal Review Panel (2020)

     The Society for Political Methodology

President (2017-2019)
Vice President and President-elect (2015-2017)
Annual Meeting Committee, Chair (2011)
Career Award Committee, Member (2015-2017)
Program Committee for Annual Meeting (2012), Chair (2011)
Graduate Student Selection Committee for the Annual Meeting (2005), Chair (2011)
Statistical Software Award Committee (2009, 2010)
Emerging Scholar Award Committee (2013)

     American Statistical Association

Journal of Educational and Behavioral Statistics Management Committee (2016-2018)

     Others

External Review Committee member, Department of Political Science, University of Rochester (2022)
External Expert, Department of Methodology, London School of Economics and Political Science (2017)

  Memberships

American Political Science Association;  American Statistical Association;  Midwest Political Science Association;  The Society for Political Methodology.

© Kosuke Imai
 Last modified: Wed Mar 20 19:10:53 EDT 2024