Andrew E. Gelman

Andrew E. Gelman is the Higgins Professor of Statistics and Professor of Political Science at Columbia University's Faculty of Arts and Sciences, where he directs the Applied Statistics Center. He holds affiliations with the Computing Systems for Data-Driven Science and Foundations of Data Science centers, and serves on the Computational Social Science Committee, reflecting his interdisciplinary impact across statistical methodology and social applications.

His research integrates advanced statistical theory with real-world problems, including voting behavior rationality, election polling variability, redistricting efficacy, criminal justice analysis (death sentence reversals, NYC police stops), small-effect estimation challenges, social network structures, environmental contamination (Bangladesh arsenic, household radon), toxicology, and medical imaging. Core methodological contributions span Bayesian analysis, multilevel modeling, survey design, experimental inference, and data visualization.

Gelman's accolades include:

• Outstanding Statistical Application award (American Statistical Association)
• Best article award (American Political Science Review)
• COPSS Presidents' Award for under-40 contributions

His seminal books—Bayesian Data Analysis (with Carlin, Stern, Rubin), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Hill), and Red State, Blue State, Rich State, Poor State (with Park et al.)—have reshaped quantitative social science pedagogy and practice. As Applied Statistics Center director, he leads cross-disciplinary teams tackling global issues like environmental health crises through rigorous statistical frameworks.

Professor Gelman actively mentors graduate students and collaborates across public health, political science, and environmental research domains, emphasizing accessible statistical education and ethical methodology application in policy-critical contexts.