Increased access to the radio frequency spectrum is critical to continued wireless innovation, yet there is limited understanding about how this valuable natural resource is being used. Measurements play a key role in understanding spectrum use and can be used to build sophisticated machine learning models for spectrum access and management. In this talk, I will present an approach to spectrum explainability based on a spectrum knowledge graph. The knowledge graph unifies relevant contextual information from a variety of sources with measurement summaries and is implemented on the Neo4j graph data platform. It can be queried to extract a wide variety of insights thus making spectrum knowledge more.
Dr. Cynthia S. Hood is currently a Fulbright Scholar at Poznań University of Technology. She is an Associate Professor in the College of Computing at Illinois Institute of Technology, where she is also the director of the Wireless Networks, Communication and Policy Research Center, and a member of Socially Responsible Modeling, Computation, and Design (SoReMo). She is also a Research Fellow in the School of Information Sciences at the University of Illinois, Urbana- Champaign. Her current research focuses on the automation of spectrum analysis. Other research interests include spectrum management, sociotechnical systems, ethics and computing in public policy.
Dr. Hood was a member of United States Representative Lauren Underwood’s (IL-14) Science, Technology & Environment Advisory Council for the 117th Congress. She has been involved in multiple National Academies of Science, Engineering, and Medicine consensus study reports. She is a recipient of a National Science Foundation CAREER Award. Dr. Hood is a senior member of IEEE and a member of ACM. She received her B.S. in Computer and Systems Engineering from Rensselaer Polytechnic Institute, her M.E. in Electrical Engineering from Stevens Institute of Technology and her Ph.D. in Computer and Systems Engineering from Rensselaer Polytechnic Institute.