Projects

With MIT AeroAstro, we are developing forecasts and decision support tools to aid air traffic controllers in avoiding the formation of persistent contrails, which are increasingly considered to have a substantial impact on climate warming.

A low-cost technology can increase the number and quality of wind and temperature atmospheric observations made by aircraft to improve forecasts.

Deploying large networks of ground-based methane detectors could help detect pipeline leaks, improve climate models, and regulate emission sources.

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 compiled a massive open-source dataset to develop deep learning models capable of detecting and predicting tornadoes.

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.