Due to data use agreements, this week's seminar is only open to researchers and students affiliated with universities, and its content cannot be posted publicly.
Alexander Volfovsky is an Associate Professor of Statistical Science at Duke University, where he also serves as co-director of the Polarization Lab. He is also an Amazon Scholar working in Supply Chain Optimization Technologies (SCOT). 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 research has been supported by the National Science Foundation, the Department of Defense, and the Templeton Foundation, among others.
This seminar will be offered IN-PERSON in SAV 409 (without a zoom option).
