Welcome
Kosuke Imai (pronounced
K sk ) 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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