This $363,931 project grant awarded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of scalable, high-performance graph-based clustering algorithms for massive datasets. The collaborative research project, led by Brown University, aims to create an open-source toolkit that enables efficient clustering of datasets with billions of entities. The researchers will focus on new algorithms that leverage graph structures and parallelism to achieve near-linear runtime performance while maintaining high accuracy. The resulting clustering toolkit will make these advanced capabilities more accessible to scientists and practitioners across various domains. No sub-awards are planned for this project, which has an award period from October 1, 2024 to September 30, 2028.
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