This inventor holds 1 USPTO granted patent. Top assignee: Elsevier, Inc.. Active years: 2020.
Company Filing History:
Years Active: 2020
Title: Matt Hobby: Innovator in Network Structure Extraction
Introduction: Matt Hobby is a notable inventor based in York, GB. He has made significant contributions to the field of network analysis through his innovative patent. His work focuses on extracting structure from large, dense, and noisy networks, which has important applications in various domains.
Latest Patents: Matt Hobby holds a patent titled "Systems and methods for extracting structure from large, dense, and noisy networks." This patent describes a method for extracting structure from networks by receiving an edge list that defines a network with nodes and edges. The method involves filtering nodes based on predetermined parameters, identifying distinct connected components, and analyzing these components for additional structures. Furthermore, it includes performing a tree traversal to generate a hierarchical structure, ultimately leading to the determination of a local modularity optimum and the generation of structural components within the network.
Career Highlights: Matt Hobby is associated with Elsevier, Inc., where he applies his expertise in network analysis. His innovative approach has positioned him as a key figure in the development of methods that enhance our understanding of complex networks.
Collaborations: Some of Matt's notable coworkers include Jacek Szejda and Peter Wooldridge. Their collaborative efforts contribute to advancing research in network structures and methodologies.
Conclusion: Matt Hobby's work in network structure extraction exemplifies the impact of innovative thinking in technology. His contributions continue to influence the field and pave the way for future advancements.