Projects

An algorithm uses camera imagery to estimate visibility for pilots flying in remote areas that lack weather sensors.

A radar and guidance system enables uncrewed aircraft systems (UAS) to avoid collisions with other aircraft, allowing the Department of Defense to operate UAS in the National Airspace System.

By compiling lightning data, satellite imagery, and numerical weather models, the GSWR provides radar-like analyses and forecasts over regions not observed by actual weather radars.

 We are developing deep learning  models  to analyze tornadic precursors in order to enhance real-time tornado prediction.   

Our model optimizes the scheduling of aerial refueling missions, saving fuel and costs for the Department of Defense.

A system that detects laser beams being shone into the sky and alerts police of their source can help protect pilots and aircraft.

An affordable radar surveillance system will help tower controllers at small airports monitor traffic even under poor visibility conditions.

A next-generation collision avoidance system will help pilots and unmanned aircraft safely navigate the airspace.