Geospatial Intelligence for the Grid
Machine learning and geospatial models that fuse imagery, sensor, and operational data to support reliability, resilience, and sustainability across the energy delivery network.
Projects
A sampling of the problem areas I work in — from monitoring greenhouse gases to building geospatial intelligence for the energy system.
Methane & GHG Emissions Monitoring
Algorithms to detect, quantify, and attribute methane and other greenhouse-gas emissions from drone- and sensor-based measurements — turning field data into actionable, defensible numbers.
CO2 Estimation from Satellite Data
Research applying machine learning to estimate carbon-dioxide concentrations from satellite observations, bridging remote sensing and data science.
Aerosol & Atmospheric Remote Sensing
Foundational research at NASA Langley on aerosol water uptake and microphysics using lidar and in-situ measurements at the DOE SGP site.