Princeton University

School of Engineering & Applied Science

Data Science: Rethinking DSP

Speaker: 
José M. F. Moura, Carnegie Mellon University
Location: 
E-Quad, B205
Date/Time: 
Friday, June 6, 2014 - 1:30am to 2:30am

<strong>Abstract:</strong>
Chris Anderson* titled provocatively his 06.23.08 piece "The End of Theory: The Data Deluge Makes the Science Method Obsolete." Data (big), computers (cloud), storage (vast), bandwidth (massive) and Google (or the likes) will find the correlations that will save the day. No (need for) causation. May be; or we might still try to explain it. Data is big, comes from all sorts of sources–social, business, urban, physical, biological, molecular. If we capture the relations among data through (arbitrary) graphs, we show how the "big data" challenge can be cast in the familiar setting of everyone’s beloved DSP, and how traditional models extend to the unstructured settings of big data. This talk will overview our progress so far extending to data defined on graphs (graph signals) traditional signal processing concepts including shifting, frequency, filtering, convolution, spectral representation, filters frequency response, linear transforms like the discrete Fourier transform. We illustrate with data drawn from social networks and the World Wide Web.
Work with Dr. Aliaksei Sandryhaila and graduate student Jonathan Mei.
*Editor in Chief of Wired Magazine.
<strong>Biography:</strong> José M. F. Moura is a visiting Professor at CUSP, NYU (2013-14). He is the Philip and Marsha Dowd University Professor at Carnegie Mellon University, with interests in statistical signal processing (SP) and data science. A sequence detector of two of his patents (co-inventor Kavcic) is found in 2.4 billion disk drives of 60% of all computers sold worldwide in the last 10 years. He cofounded SpiralGen that commercializes the Spiral technology (www.spiral.net) under license from CMU. He was an IEEE Board Director (2012-2013), President of the IEEE Signal Processing Society (SPS), and Editor in Chief for the Transactions on SP. Moura received the IEEE Signal Processing Society Technical Achievement Award and the IEEE Signal Processing Society Society Award for outstanding technical contributions and leadership in SP. He is a Fellow of the IEEE, a Fellow of AAAS, a corresponding member of the Academy of Sciences of Portugal, and a member of the US National Academy of Engineering.