Funded by the US National Science Foundation.
Collaborative Research:
OAC Core Awards OAC:2402559 (7/5/2024) & OAC:2402560 (7/5/2024)
Investigators:
Tandy Warnow, University of Illinois Urbana-Champaign (Principal Investigator OAC-2402559)
David Bader, New Jersey Institute of Technology (Principal Investigator: OAC-2402560)
George Chacko, University of Illinois Urbana-Champaign (co-Principal Investigator OAC-2402559)
Key Personnel:
Minhyuk Park, University of Illinois Urbana-Champaign
Mohammad Dindoost, New Jersey Institute of Technology
Zhihui Du, New Jersey Institute of Technology
Community detection methods enable an understanding of the structure of networks at multiple scales. While many methods exist, only a few are able to scale to large networks and/or are implemented in large computational infrastructure. As we have recently shown, even those that scale to large datasets, fail to reliably produce well-connected clusters. Finally, given that the choice of clustering method depends on both the network being analyzed and the question of interest, providing the domain specialist a choice of multiple clustering methodologies within a common framework for exploratory data analysis, is essential. This project will make substantial advances on these challenges through the coordinated development of advanced cyber-infrastructure, scalable to very large networks, that offers multiple options for community detection, search, and extraction. The infrastructure will be accessible across platforms ranging from laptops to multi-node clusters with distributed memory.
Related Research (not supported by this award)
Anne et al. (2025) RECCS: Realistic Cluster Connectivity Simulator for SyntheticNetwork Generation (submitted Advances in Complex Systems)
Park et al. (2025) Improved Community Detection using Stochastic Block Models (submitted. PLOS Complex Systems)
Anne et al. (2024) Synthetic Networks That Preserve Edge Connectivity Accepted. CNA 2024
Park et al. (2024) Improved Community Detection using Stochastic Block Models Accepted CNA 2024
Tabatabaee et al. (2024) FastEnsemble: A new scalable ensemble clustering method Accepted CNA 2024
Park et al. (2024) Well-Connectedness and Community Detection PLOS Complex Systems