Gonzalo Mateos’ work selected for a 2017 IEEE Signal Processing Society’s Young Author Best Paper Award
January 24, 2018
Work by Gonzalo Mateos, assistant professor of electrical and computer engineering, has been recognized with a 2017 IEEE Signal Processing Society’s Young Author Best Paper Award for the paper: Morteza Mardani, Gonzalo Mateos, and Georgios B. Giannakis, “Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors” IEEE Transactions on Signal Processing, Vol. 63, No. 10, May 2015 (http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7072498).
The paper puts forth innovative, real-time algorithms to extract actionable information from highly incomplete, multi-dimensional streaming data structures (known as tensors), and facilitate data imputation as a byproduct. Going beyond mainstream applications of data completion such as those encountered with e.g., movie recommendation systems, algorithms in the paper are shown to positively impact Internet traffic monitoring tasks as well as image reconstruction quality when applied to in vivo dynamic cardiac magnetic resonance imaging (MRI) data.
A full list of the 2017 IEEE Signal Processing Society awardees can be found at https://signalprocessingsociety.org/get-involved/award-recipients.