Distinguished Seminar: José M.F. Moura, Philip L. and Marsha Dowd University Professor at Carnegie Mellon
All dates for this event occur in the past.
Details: Tuesday, Feb. 5 from 4 p.m. to 5 p.m. in Dreese lab Room 260. Coffee and cookies provided.
Title: “Graph Signal Processing”
ABSTRACT: Traditionally, Signal Processing deals with time series, images, video, and data indexed by time ticks and pixels. The structure of the indexing set is taken for granted. The last few years have seen an explosion of applications where signals and data are now indexed by social agents, genes, customers, or some other enumeration suggested by the application. We will present Graph Signal Processing (GSP) that extends to data (signals) arising from these various domains the essential concepts and methods of traditional Signal Processing—signal model, shift, filtering, convolution, spectral analysis, Fourier transform, filter frequency response. We apply GSP to deep learning and to uncover dependencies among data and illustrate it with datasets drawn from physical to social networks.
BIO: José M. F. Moura is the Philip L. and Marsha Dowd University Professor at CMU, with interests in signal processing and data science. A detector in two of his patents with Alek Kavcic is found in over 60% of the disk drives of all computers sold worldwide in the last 15 years (4 billion and counting)–leading to a US
$750 Million settlement between CMU and Marvell. He is the 2019 IEEE President and CEO. He was Editor in Chief for the Transactions on SP. Moura received the IEEE Signal Processing Society Technical Achievement Award and Society Award. He is Fellow of the IEEE, AAAS, and the US National Academy of Inventors, corresponding member of the Academy of Sciences of Portugal, and member of the US National Academy of Engineering. He received the Grã Cruz of the Ordem do Infante D. Henrique bestowed to him by the President of the Republic of Portugal.