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NSF Awards Lau Close to $371,000 to Advance Graph Signal Processing

September 10, 2018

The project presents a collaborative research and education effort in graph signal processing.

Daniel Lau, Kentucky Utilities Professor in the Department of Electrical and Computer Engineering, has received a nearly $371,000 grant for a project titled “Blue-Noise Graph Sampling.” The abstract is below.

“This project presents a collaborative research and education effort in graph signal processing where interesting phenomena in nature can often be captured by graphs since objects and data are invariably interrelated in some sense. Social networks, ecological networks, and the human brain are a few examples of such networks. A feature that these networks of interest have in common, is that they define very large graphs. Algorithms used to compute properties of complete graphs, rapidly become impractical when the graphs under study become very large. Graph sampling thus becomes essential. The research explores a somewhat radical departure from the prior work on graph sampling and is based on the notion of stochastic sampling in irregular sampling grids. In concert with the advancing the scientific goals of the project, the investigators will also jointly develop a short course on graph signal processing and its applications so as to introduce this emerging field to a broad set of students.”

Lau joined the department in 2001.