His research focuses on causal and counterfactual inference and their applications to data-driven fields. Bareinboim received a Ph.D. in Computer Science from UCLA working with Judea Pearl. His doctoral thesis was the first to propose a general solution to the problem of “data-fusion” and provides practical methods for combining datasets generated under different experimental conditions. Bareinboim’s recognitions include IEEE AI’s 10 to Watch, the Dan David Prize Scholarship, the Yahoo! Key Scientific Challenges Award, and the 2014 AAAI Outstanding Paper Award.