The rapid growth of network data across science, engineering, business, and society has created new opportunities and challenges for understanding community structure in large-scale networks. Join us as we explore the next generation of scalable methods, computational infrastructure, and synthetic data frameworks for discovering community structure in massive networks.
Community Detection at Scale (CDS2027) brings together researchers and practitioners working on finding communities in large networks: algorithms, theory, software, and applications.
We invite researchers, students, practitioners, and computational scientists to attend a two-day workshop focused on community detection in very large networks, scalable HPC approaches for graph analytics, and synthetic network generation and applications. The workshop will bring together experts in network science, graph algorithms, data analytics, cyberinfrastructure, and domain applications to explore emerging methods and opportunities for large-scale network analysis.
The workshop is associated with the NSF-funded project Cyber-Infrastructure for Community Detection, Extraction, and Search in Large Networks led by researchers at the University of Illinois Urbana-Champaign and New Jersey Institute of Technology.