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Alexander Volfovsky is an Associate Professor of Statistical Science at Duke University. His research primarily focuses on the theory and methodology of network analysis and causal inference, exploring the statistical and computational tradeoffs in applications related to the social sciences. He investigates modern data streams that diverge from traditional paradigms of independent observations, emphasizing the inclusion of complex dependencies among observations, such as the interference in studies of causal effects. Additionally, his work addresses quantities of interest like probabilities related to edge formation in networks. Volfovsky has received funding for several significant research projects, including a co-principal investigator role in a project aimed at increasing open-mindedness and facilitating productive dialogue through AI agents, and leading research on EEG-guided treatments for acute brain injuries. His academic journey has been enriched through his education at prestigious institutions, culminating in a Ph.D. from the University of Washington.
Department of Biomedical Engineering (MS program)