In this proposal, the PI and team will focus their research in two areas. The first will be to understand the implications of deep learning algorithms and their performance on foundational assumptions for the popular potential outcomes model. The second part of the grant will deal with developing scalable algorithms for causal effect estimation. New computationally scalable algorithms for causal effect estimation will be developed as part of this proposal.