FIND Seminar: Anna Scaglione: A User Guide to Low-Pass Graph Signal Processing and its Applications
Phillips Hall 233
Foundations of Information, Networks, and Decision Systems (FIND) presents:
School of Electrical and Computer Engineering
A User Guide to Low-Pass Graph Signal Processing and its Applications
The notion of graph filters can be used to define generative models for graph data. In fact, the data obtained from many examples of network dynamics may be viewed as the output of a graph filter. With this interpretation, classical signal processing tools such as frequency analysis have been successfully applied with analogous interpretation to graph data, generating new insights for data science. What follows is a user guide on a specific class of graph data, where the generating graph filters are low-pass, i.e., the filter attenuates contents in the higher graph frequencies while retaining contents in the lower frequencies. Our choice is motivated by the prevalence of low-pass models in application domains such as social networks, financial markets, and power systems. We illustrate how to leverage properties of low-pass graph filters to learn the graph topology or identify its community structure; efficiently represent graph data through sampling, recover missing measurements, and de-noise graph data; the low-pass property is also used as the baseline to detect anomalies.
Anna Scaglione is a Professor at Cornell Tech in the Electrical and Computer Engineering Department at Cornell University. Her research interest is in novel digital technology for smart infrastructures and data science. In her work she draws tools from signal processing, communication theory, network science, optimization and power systems. Her research has been supported by NSF, DoD (ONR and ARO), DoE and ARPA-e. She is an IEEE fellow since 2011 for her contributions to signal processing and communication theory. She received the 2000 IEEE Signal Processing Transactions Best Paper Award, the NSF CAREER grant in 2002, is co-recipient of the 2013 IEEE Donald G. Fink Prize Paper Award for the best review paper in that year across all IEEE publications in 2013, and the 2013 IEEE Signal Processing Society Young Author Best Paper Award (with her PhD student Lin Li) . She was distinguished lecturer for the IEEE Signal Processing Society in 2019-2020. She holds a PhD degree from the University of Rome “La Sapienza” in Italy, and she was a postdoctoral scholar at the University of Minnesota.