Project leader in neuromorphic computing, applied machine learning, and image and signal processing projects in support of national security. My interests are in machine learning, computer vision, remote sensing, SWaP constrained applications, resolution enhancement, and analysis of image and video systems. In 2017, with support from the Information Science and Technology Institute (ISTI) and The Center for Nonlinear Studies (CNLS) at LANL, I co-founded an Applied Machine Learning Research Internship program at LANL to attract graduate students in this important research field to the Lab.

My dissertation, "Resolution Enhancement of Muli-look Imagery," was done at Los Alamos under the Multispectral Thermal Imager satellite project. I was part of the Geo team, responsible for resampling and registration of data from MTI.

Contributes technical expertise in remote sensing and image processing to the overall image collection and exploitation process. Responsible for introducing image processing techniques to enhance the commercial satellite imagery used by IAEA analysts, including electro-optical (EO) and synthetic aperture radar (SAR). Provides expertise in the use of multispectral data sources to enhance the capabilities for site analysis. Liaises with commercial vendors and/or contractors to explore additional sensors of interest and image enhancement algorithms for state infrastructure analysis. Specialist in remote sensing, computer vision, and machine learning / deep learning.