This $363,931 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports a collaborative research project between multiple institutions to develop scalable clustering algorithms for processing large datasets. The goal is to create new clustering algorithms that can efficiently group billions of data points into meaningful clusters, addressing the limitations of current methods. The work will produce an...
This $364,000 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports a collaborative research project to develop scalable, high-performance graph-based clustering algorithms for large datasets. The project aims to create a publicly available toolkit that enables efficient, accurate clustering of datasets with billions of entities. Key focus areas include new algorithms for graph construction and...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant award, with the federal assistance program number CFDA 47.070, will provide $268,591 to Rutgers, The State University to conduct research on the fundamental limits of approximating clustering problems. The project aims to establish tight inapproximability results for key clustering objectives like k-means, k-median, and k-center under various metrics. The research will leverage tools from...
The National Science Foundation awarded a $116,000 Project Grant to the University of Massachusetts Dartmouth under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The two-year award will support research from September 2021 to August 2023 to develop computationally efficient fuzzy clustering algorithms for distributed big data applications. As the parent organization of the awardee, the University of Massachusetts will oversee delivery of research...
This $150,000 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will fund the development of new clustering techniques and software packages at San Jose State University. The awardee will create a family of versatile mixture models to analyze mixed-type data with asymmetry, outliers, and missing values. Novel statistical approaches and latent class models will allow the techniques to handle high-dimensional, continuous, discrete,...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award provides $364,000.00 to the Massachusetts Institute of Technology (MIT) from October 1, 2024 to September 30, 2028. The project aims to develop scalable, high-performance graph-based clustering algorithms capable of efficiently processing massive datasets with billions of entities. Key objectives include creating new algorithms for graph clustering and...
This National Science Foundation (NSF) Project Grant award, funded under the Computer and Information Science and Engineering program (CFDA 47.070), provides $110,000 to the University of Illinois to conduct research on geometric data clustering. The key objectives are to: (i) identify sufficient geometric conditions for clustering data using a small number of centers, (ii) develop algorithms to approximate the optimal number of clusters, and (iii) explore efficient techniques for finding a...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $250,000 to the New Jersey Institute of Technology (NJIT) for a 3-year collaborative research project focused on developing advanced community detection and graph clustering methods for analyzing large network datasets. The key objectives are to create highly efficient software implementations of new community detection algorithms that can...
The University of California, San Diego received a $489,206 Project Grant award from the National Science Foundation on June 1, 2021 to support research titled "SMALL: NEW DIRECTIONS IN CLUSTERING: INTERACTIVE ALGORITHMS AND STATISTICAL MODELS." The award period runs through October 31, 2022. The funding supports the Computer and Information Science and Engineering program, which aims to advance computing, communications, and information science through investigator-initiated...
This three-year, $359,998 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will fund the development of statistical and computational tools for analyzing high-dimensional heterogeneous data. Specifically, the awardee, Columbia University, will create new methodologies for clustering and identifying latent structures in complex data involving multiple attributes and relationships. The research has three parts. The first will develop...