Nathan Kallus

Nathan Kallus is an associate professor of operations research and information engineering at Cornell Tech and Cornell Engineering. Kallus’s research interests include causal inference, especially when combined with machine learning; the statistics of optimization under uncertainty; sequential and dynamic decision making; and algorithmic fairness. He is the author of the book “Applied Causal Inference Powered by ML and AI.”

Kallus holds a Ph.D. in operations research from the Massachusetts Institute of Technology and a B.A. in mathematics and a B.S. in computer science from the University of California, Berkeley. Before coming to Cornell, Kallus was a visiting scholar at the University of Southern California’s Department of Data Sciences and Operations. He was also a postdoctoral associate at MIT’s Operations Research and Statistics group.