Trusted and exPlainable Artificial Intelligence for Saving Lives (TruePAL) Technology for First Responder Safety

Fatalities caused by emergency vehicle collisions are 4.8 times higher for emergency responders than the national average. The Trusted and exPlainable Artificial Intelligence for…

Volcano SensorWeb

NextGen Advanced Methods: ATCSCC Webinar Speech2Text and Analysis

The Advanced Methods project explores the use of innovative and emerging technologies to drive post operational analysis of Traffic Management for aircraft. Technologies such as m…

Classification of features in Crew Earth Observations imagery

Feature classification in Crew Earth Observations imagery of the following classes: Earth limb, lightning, the Moon, aurora, cities (64 cities, day/night), ISS equipment. For depl…

Cloud masks from Crew Earth Observations imagery

Generation of cloud masks via segmentation in Crew Earth Observations (Crew Earth Observations) images. For deployment on the Gateway to Astronaut Photography to supplement search…

Comment Analytics Dashboard

Developed using Python and R, the Comment Analysis Dashboard is designed to visualize sentiment scored data provided by SF to better understand how crew members feel on a day-to-d…

NextGen Data Analytics: Letters of Agreement

Today, operation constraints are documented via Standard Operating Procedures (SOP) and Letters of Agreement (LOA) and are not made available to the public in a consistent manner.…

Crew Earth Observations automated georeferencing/geolocation

Automated georeferencing of Crew Earth Observation images. For deployment on the Gateway to Astronaut Photography.

Machine Learning for RFID (Radio Frequency Identification) tag localization to support logistics

Currently have two production machine learning approaches to tackle RFID (Radio Frequency Identification) tag localization in the highly reflective environment imposed by the Inte…

Noise suppression in Human Spaceflight audio systems

Noise. Is. Aggravating. Especially on voice and video calls. It’s certainly an unwelcome party to most conversations, but it has always been around.

Adaptive Neural Network Molecular Dynamics

ML approach, based on artificial neural networks (ANNs) is used in atomistic simulations to efficiently reproduce the very complex energy landscape resulting from the atomic inter…

Aerosol and Cloud Identification in SAGE III/ISS Aerosol Extinction Profiles

This work uses machine learning techniques to classify aerosols in SAGE (Stratospheric Aerosol and Gas Experiment) III / ISS (International Space Station) Aerosol Extinction Profi…

AMP: An Automated Metadata Pipeline

In this work, we combine ontologies and machine learning to auto-generate robust, semantically consistent, variable-level metadata records for large NASA satellite collections, an…

Application of High-Dimensional Fuzzy K-mean Cluster Analysis to CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) / CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observatory) Version 4.1 Feature Classifications

This project uses Fuzzy K-means clustering (unsupervised learning) to validate the cloud-aerosol discrimination algorithm used in the publibly-distributed CALIOP (Cloud-Aerosol Li…

CERES FluxByCldTyp Data Product Narrowband-to-Broadband Algorithm Improvement Through Deep Neural Network (DNN)

Apply DNN (Deep Neural Networks) to the CERES (Clouds and the Earth's Radiant Energy System) Flux by Cloud Type data narrowband-to-broadband algorithms to improve shortwave and lo…

Cloud Detection Neural Network

Detection of clouds below and above aircraft to reduce cloud contamination and improve NASA passive remote sensing of aerosols, oceans and lands from aircraft.

Combining Satellite and Ground-based Observations to Improve Cloud Ceiling Observations over CONUS for Aviation Weather

A k-nearest neighbors method is applied to use satellite observations to extend sparse ceilometer observations at surface stations to high spatiotemporal resolutions over CONUS (C…

Detection of multi-layered clouds from multispectral MODIS/VIIRS data using an artificial neural network trained with CALIPSO-CloudSat data.

Detection of multi-layered clouds from multispectral MODIS (Moderate Resolution Imaging Spectroradiometer) / VIIRS (Visible Infrared Imaging Radiometer Suite) data using an artifi…

Developing Quantum Reservoir Computing Hardware and Software for Deep Learning

This study uses integrated photonic circuits, mode-locked lasers and quantum optics to perform fast computing that use that to train the recurrent neural network deep learning thr…

Estimation of Multilayered Cloud Properties from Geostationary Satellite Imager Data

A deep neural network is developed and applied to geostationary satellite imagery data to identify and retrieve characteristics of multi-layered clouds for potential use in weathe…

Estimation of Multilayered Cloud Properties from Low-Earth-Orbit Satellite Imager Data

An artificial neural network is developed and applied to satellite imagery data to identify and retrieve characteristics of multi-layered clouds for potential use in weather and c…

Geostationary Satellite Sounder Pathfinder Project for 4-D Atmospheric Thermodynamics and Winds

A k-nearest neighbors technique, coupled with an advanced data assimilation system are applied to hyperspectral infrared and geostationary satellite imager data to provide high sp…

Identifying Aerosol Subtypes from CALIPSO Lidar Profiles Using Deep Machine Learning

Applies convolutional neural networks (supervised learning) to automatically identify the presence of different aerosol species (e.g., dust and smoke) in CALIPSO lidar backscatter…

Identifying flaws in manufacturing of composites

Inspection for manufacturing flaws makes up 40% of fabrication time so if that time could be reduced it would have a significant impact on overall manufacturing time.  That doesn’…