Project Grant 2337916

This Project Grant award of $462,500.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to advance the state-of-the-art in causal artificial intelligence (AI) methods. The key objectives are to: 1) Automate components of the causal analysis pipeline and develop robust data-driven estimation procedures to enable more decision-makers to leverage causal AI systems; 2) Integrate education and research by developing open-source software tools, fostering academia-industry collaborations, and creating educational materials including coding tutorials, lecture notes, and textbooks. The research will focus on areas such as finite sample analysis of causal estimation, automated confidence interval construction, causal model selection with rigor, leveraging large language models for domain assumptions, and algorithmic approaches for automated causal effect identification. The ultimate goal is to provide accessible tools and educational resources that reduce barriers to applying causal AI across various domains. This 5-year award to Stanford University commenced on Aug 1, 2024.