Elias Bareinboim is an associate professor in the Department of Computer Science and the director of the Causal Artificial Intelligence Lab at Columbia University. Prior to joining Columbia, he was an assistant professor at Purdue University. Before that, he obtained his Ph.D. in Computer Science at the University of California, Los Angeles, advised by Judea Pearl. Elias is broadly interested in Artificial Intelligence, Machine Learning, Statistics, Robotics, Cognitive Science, and Philosophy of Science.
His research focuses on causal inference and its applications to data-driven fields (i.e., data science) in the health and social sciences as well as artificial intelligence and machine learning. He is particularly interested in understanding how to make robust and generalizable causal and counterfactual claims in the context of heterogeneous and biased data collections, including due to issues of confounding bias, selection bias, and external validity (transportability).
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