This $462,500 Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering program (CFDA 47.070), supports the development of advanced causal inference methods for data-driven decision making. Key products and services to be delivered include: Automated and robust causal AI systems that integrate machine learning and causal inference techniques to enable more decision-makers to leverage causal analysis. The project will...
This $574,140 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of novel algorithms to extract causal relationships from diverse, unstructured datasets. The project aims to address limitations of current causal discovery methods that rely heavily on interventional data, by creating algorithms that can leverage common causal knowledge across datasets from different environments....
The National Science Foundation (NSF) awarded a $543,995 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the Regents of the University of Michigan. This 3-year grant, starting on September 1, 2024, aims to develop statistical tools to assess the societal impacts of predictive models and policy recommendations in order to improve social welfare. The technical focus is on leveraging the phenomenon of "performativity", where the predictive...
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...
This $130,291 Project Grant was awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to Cornell University on July 1, 2024. The grant supports the development of new methods for causal inference that address interference arising from network interactions and time dynamics. This research aims to enhance randomized experimentation techniques used across fields like natural and social sciences, engineering,...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award, totaling $299,392, aims to build a collaborative mechanism for academia, industry, and the public sector to co-design research and development (R&D) directions for data systems and artificial intelligence (AI) to address scientific and societal challenges. The project, led by the Regents of the University of Michigan, will bring together data science and...
Michigan State University was awarded a $239,960 Project Grant from the National Science Foundation Division of Computing and Communication Foundations under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The grant will support research from July 1, 2023 to December 31, 2024 to develop techniques combining formal reasoning and artificial intelligence to discover causal relationships between medical events. Specifically, the university will investigate...
The National Science Foundation awarded a $250,000 Project Grant to the University of Michigan under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The three-year award will support research into a new paradigm for distributed information processing, simulation and inference in networks through application of the "law of small numbers." The University of Michigan will leverage its expertise in computing and communications foundations to...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) Project Grant award of $175,000 to the Regents of the University of Michigan - Flint will support research to understand how the framing of news stories changes as they are shared on social media. The research team will develop a dataset of news stories and social media posts, then use machine learning models to analyze how the framing of events evolves as content is...
This $150,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support the development of foundational principles, algorithms, and tools for causal decision-making systems. Researchers at Columbia University will enrich traditional artificial intelligence formalism with causal modeling to enable more efficient, robust, and explainable decision-making by autonomous systems. Key deliverables include integrating...