Air Quality Analytics Collaborative Framework (ACF)

Integration of cloud-scale machine learning algorithms: - ML algorithm cloud-services, like SageMaker and TensorFlow, can access harmonized data sets. - Scientists can easily create machine learning analysis workflows using these algorithms. - ML is powerful tool for AQ predictions, but hard to use at scale across data sets. Integration of models with workflows, esp GeosCHEM. - Facilitates inclusion of atmospheric chemistry/transport models into analysis workflows. - Model outputs are available to other analysis workflows - Model can use harmonized data sets for its inputs.

Advance Earth system science knowledge through the identification, development, and demonstration of innovative information systems technologies

This is early/mid-stage (TRL 4) — 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.