Brian Bue is a research technologist in the Machine Learning and Instrument Autonomy group at the Jet Propulsion Laboratory. He has 10 years of experience developing and deploying machine learning techniques designed for ground-based and onboard applications in Earth science, planetary science, and astronomy.

A central focus of his work has been the development/deployment of automated data processing and classification algorithms for imaging spectroscopy/hyperspectral imaging platforms, including the first real-time, model-based atmospheric calibration system deployed onboard an aircraft. His Ph.D. thesis work focused on methods to effectively quantify the similarity of hyperspectral image pixels measured under differing imaging conditions or across sensors. He released much of his work as the lead developer of the JPL Hyperspectral Image Interactive Holistic Analysis Toolkit (HiiHAT), an open-source ENVI/IDL toolkit designed for the analysis of imaging spectrometer data.

Automated surface feature detection using both imaging and terrain data has been another major focus of his research. His computer vision-based crater detection work with Tom Stepinski (Univ. of Cincinnati) produced a global catalog of 75,919 Martian craters, which included, for the first time, their depths, which subsequently confirmed establieshed theories about the distribution of subsurface ice on Mars. He is currently using similar techniques to search for subsurface water on Mars using HiRISE images and terrain data, and to characterize urban areas according to their damage risk potential due to natural disasters such as hurricanes and earthquakes.

More recently, his research has involved automated quality assurance and anomaly detection for interferometric synthetic aperture radar (InSAR) images, astronomical transient detection for synoptic imaging surveys, time series inference for predicting air traffic delays, and onboard target detection to aid exploration of primitive bodies such as asteroids and comets. Brian holds a Ph.D. in Electrical and Computer Engineering from Rice University.