This $174,118 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop new algorithms and software tools to enable robust causal inference from observational data, even when faced with model misspecification and uncertainty. The project seeks to build methods that allow data scientists to propose multiple causal models and combine effect estimates, as well as perform model selection that is robust to unmeasured confounding and data issues. This work aims to improve the reliability of decision-making processes across fields where controlled experiments are infeasible. The award was made to President & Trustees of Williams College, a private liberal arts institution, on June 1, 2024, and is scheduled for completion by May 31, 2026. No sub-awards are planned under this grant.
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