Utilizing Artificial Intelligence/Machine Learning for Improving Ionospheric Space Weather Forecast

Completed TRL 2 (started at 2, targeting 3)

Description

Use artificial intelligence and machine learning together with physical modeling and GNSS TEC measurements to improve the accuracy and reliability of space weather models.

Benefits

Revolutionize the understanding; monitoring; and forecasting of the thermosphere/ionosphere. Provide a more precise and timely space weather forecast.

Details

Technology area	Human Health, Life Support, and Habitation Systems > Radiation > Space Weather Prediction
Program	Center Innovation Fund: JPL CIF (JPL CIF)
Lead organization	Jet Propulsion Laboratory, Pasadena, CA
Start date	2024-10-01
End date	2025-09-30

Project contacts

Listed on TechPort itself — the most direct way to ask about this specific project.

George A Hajj — george.hajj@jpl.nasa.gov
Attila Komjathy — attila.komjathy@jpl.nasa.gov
Olga Verkhoglyadova — olga.verkhoglyadova@jpl.nasa.gov
Xiaoqing Pi — xiaoqing.pi@jpl.nasa.gov

How to get involved

This is early/mid-stage (TRL 2) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

None of these are guaranteed paths for this specific project — TechPort itself doesn't have an "apply" button. Reaching out to the contact(s) above with a specific question is usually the fastest way to find out what's actually open.