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Kosuke Imai (pronounced kō-ˈskā ē-mī) is Professor in the Department of Government and the Department of Statistics at Harvard University. He is also an affiliate of the Institute for Quantitative Social Science. Before moving to Harvard in 2018, Imai taught at Princeton University for 15 years. Imai specializes in the development of statistical methods and machine learning algorithms and their applications to social science research. His areas of expertise include causal inference, computational social science, and survey methodology. Imai is the author of Quantitative Social Science: An Introduction (Princeton University Press, 2017). In addition, Imai leads the Algorithm-Assisted Redistricting Methodology Project (ALARM) and served as an expert witness for several high-profile legislative redistricting cases. Outside of Harvard, Imai served as the President of the Society for Political Methodology from 2017 to 2019.

His current research interests include: data-driven policy learning and evaluation, causal inference with high-dimensional and unstructured treatments (e.g., texts, images, videos, and maps), GenAI and causal inference, human and algorithmic decision-making, fairness and racial disparity analysis, algorithmic redistricting analysis, data fusion and record linkage, census and privacy.

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