Speaker: Dr. Dennis J. Lee, Computer Scientist,  Sandia National Laboratories

Seminar Topic: Compressive sensing for hyperspectral imaging

Abstract of Talk: Hyperspectral sensors measure a portion of the electromagnetic spectrum. They allow us to study how objects interact with light based on the wavelength of energy recorded. Applications include construction, agriculture, energy, and government. Compressive sensing is a technique to reduce the number of measurements. I present a novel hyperspectral sensor based on the theory of compressive sensing. The reconstruction algorithms recover the hyperspectral signal from measured data. I discuss various approaches to reconstruction, including optimization and neural networks. Machine learning will classify the raw and reconstructed hyperspectral data. This presentation will provide a glimpse into current research on hyperspectral imaging.

Biographical Sketch of the Speaker:  Dennis Lee is a computer scientist in a Remote Sensing group at Sandia National Laboratories. His group specializes in developing state of the art technologies for remote sensing in the areas of optimized digital processing, real-time decision algorithms, high performance processing, remote distributed data processing architectures, rapid high consequence technology insertions for remote sensing applications, and remote sensing system engineering. He conducts research related to signal processing, statistics, and optics. He joined Sandia in 2015 after receiving his Ph.D. in Electrical and Computer Engineering from Purdue University.