Alexander Volfovsky is an Associate Professor of Statistical Science at Duke University, where he also serves as co-director of the Polarization Lab. His research lies at the intersection of causal inference, network analysis, and machine learning, with applications to understanding social behavior, online interactions, and decision-making in complex systems. He develops novel statistical methodologies for estimating causal effects in the presence of interference, modeling relational data, and designing adaptive experiments. Volfovsky’s work often bridges methodological innovation with large-scale empirical studies, integrating tools from Bayesian statistics, randomized experiments, and computational social science. His recent projects focus on human–AI interaction, trust calibration, and the design of artificial agents that foster constructive discourse. His research has been supported by the National Science Foundation, the Department of Defense, and the Templeton Foundation, among others.