Archives.gov AI search
The AI is intended to solve the problem of "unstructured data challenges" in a vast, complex catalog by replacing traditional literal-match search with semantic technology that un…
Develop a Natural Language Based Chat Interface (like ChatGPT) to Interact With the Archival Documents
The AI is intended to solve the problem of high barriers to entry for historical research by replacing complex database queries with a natural language interface that allows users…
Automated Data Discovery and Classification Pilot
The AI is intended to solve the problem of inefficient manual data governance and risk assessment by testing automated data classification techniques to organize unstructured data…
Anomaly Detection and Precursor Identification in UAV flight data
This project is using past algorithms developed by the NASA ARC (Ames Research Center) Data Sciences Group and modifying them with application to identifying previously-unknown an…
ExoMiner discovery of ExoPlanets via data from the Kepler and TESS space telescopes
ExoMiner is being used to statistically validate exoplanets detected by the Kepler space telescope and to identify promising exoplanet candidates for the TESS space telescope
Earth Information System Fire Pilot
EIS-Fire developed a visualization and analysis data portal providing access to a variety of fire data products in a cloud-optimized, analysis-ready format. The team also develope…
Enabling Autonomous Differential Drag Control and Attitude Maneuvering Using Onboard Artificial Intelligence (AI) for SmallSat Distributed Space Missions (DSMs)
This work is in enabling Autonomous Differential Drag Control and Attitude Maneuvering Using onboard Artificial Intelligence (AI) for SmallSat Distributed Space Missions (DSMs). A…
Explainable and robust deep semi-supervised model for multi-class anomaly detection in flight data
This model is a semi-supervised deep learning based anomaly detection for aircraft flight data. It is designed to work when a small subset of data is reviewed and labeled by exper…
Forest responses to climate change
This work explores a variety of Physics-Guided ML techniques to contribute to terrestrial ecosystem and carbon cycle modeling and related fields.
From Single Spacecraft to Synchronized Swarms: Fault Diagnosis for Distributed Spacecraft Mission Resilience
From Single Spacecraft to Synchronized Swarms: Fault Diagnosis for Distributed Spacecraft Mission Resilience. This project is in AI/ML-assisted fault detection and diagnosis to co…
HEASARC X-ray Spectra and Light Curve data sets
This work creates and makes available X-ray Spectra and Light Curve data sets for ML analysis from the High Energy Astrophysics Science Archive Research Center (HEASARC), which in…
High Rate Digital Spectrometer Enhancement with Neural Network AI
As spaceborne spectrometer increases in spectral resolution, the growth in spectral data volume and the limited space to Earth communication bandwidth are prone to be a problem fo…
High Resolution Earth and Planetary Atmospheric Predictions using Machine Learning
We are developing a machine learning (ML) tool that can predict high-resolution in situ atmospheric conditions using relatively lower resolution remote data e.g., from an orbiting…
Anomaly detection in aeronautics data with quantum-compatible discrete deep generative model
Our team developed high-performance unsupervised deep machine-learning models for the detection of flight-operations anomalies. The models’ engineered-feature (latent) spaces are…
HyperMapping with Hyperspectral Precise Pointing Optical Sensor (HYPPOS) for Decadal Survey Mission Pathfinder Activities
This work uses HyperMapping techniques on Hyperspectral Precise Pointing Optical Sensor (HYPPOS) data for Decadal Survey Mission Pathfinder Activities. The effort is developing AI…
Knowledge Capture: helionauts.org
This work uses natural language processing to perform text-based knowledge capture for the helionauts.org community, which is a cloud-based community of practice for Heliophysics…
M4OPT: Multi-Mission Multi-Messenger Observation Planning Toolkit
M4OPT: Multi-Mission Multi-Messenger Observation Planning Toolkit. This work includes considerations for data integration and use across multiple Science missions and leveraging m…
Machine Intelligence for Small Satellites
The MAtISSE project seeks to develop a new approach to rapid, real-time extraction and classification of photometric light curves using a modern differencing technique and advance…
Machine Learning of Ocean Worlds Laboratory Analog Seawater Volatiles
This work focuses on algorithm-development for software that can predict the composition of an ocean using mass spectra of volatile gases analyzed.
MERRAMax Automated feature selection
There is growing interest in using Intergovernmental Panel on Climate Change (IPCC)-class climate model outputs in ecological research. These models provide realistic, global repr…
Multi-temporal analytic center framework
Multi-temporal analytic center framework. This is an integrating mechanism rather than a specific AI or ML technology.
Optimization of Machine Learning Algorithms for Lidar to Detect Aerosols, Clouds, and the PBL (Planetary Boundary Layer)
Optimization of Machine Learning Algorithms for Lidar to Detect Aerosols, Clouds, and the PBL (Planetary Boundary Layer)
Parameter estimation, emulator building, model tuning and sensitivity analysis of the ocean carbon cycle using ML
This work explores neural networks and other ML techniques for Earth Science topics and data sets related to global carbon cycle, ocean circulation, air-sea interactions and clima…
PIC-ASIC Spectrometer Demonstration for Ultrawideband and Hyperspectral Microwave Sounding
This family of technologies can provide extremely small multi-sensor capabilities in areas such as ultrawideband and hyperspectral sensing.