Elias is an associate professor in the Department of Computer Science and the director of the Causal Artificial Intelligence Lab at Columbia University. He obtained his Ph.D. under Judea Pearl from the University of California, Los Angeles, Department of Computer Science. He is broadly interested in Artificial Intelligence, Machine Learning, Statistics, Robotics, Cognitive Science, and Philosophy of Science.
Elias’ 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, dataset shift, and external validity (transportability).