Amelia Earhart AI Search
The AI is intended to solve the manual search limitations when processing massive historical datasets by using Natural Language Processing to accurately locate and declassify spec…
AI Pilot Project to Screen and Flag for Personally Identifiable Information (PII) in Digitized Archival Records
The AI is intended to solve the problem of manual processing bottlenecks and privacy risks by automating the identification and redaction of sensitive personal information within…
AI based Semantic Search for National Archives Catalog (aka ArchiAI)
The AI is intended to solve the problem of "unsophisticated" keyword-based search limitations by implementing semantic search that understands user intent and historical context,…
Auto-fill of Descriptive Metadata for Archival Descriptions
The AI is intended to solve the problem of the "descriptive gap" created by labor-intensive manual cataloging by automatically generating metadata and summaries from document cont…
Topic Summarizer and Entity Extraction using AI
The AI is intended to solve the problem of unsearchable digital collections caused by massive descriptive backlogs, automating the creation of metadata for billions of digital obj…
Create an AI based knowledge articles user interface for working with CRG documents
The AI is intended to improve the case processing by providing staff with an automated retrieval tool that navigates the complex Case Reference Guide to deliver instant, accurate…
EOP 42 Search PoC using AI Based Semantic Search
The AI is intended to solve the problem of inefficient information retrieval within Presidential email archives by testing whether AI-driven semantic search can understand context…
Freedom of Information Act (FOIA) Discovery AI Pilot
The AI is intended to solve the problem of larger FOIA backlogs and manual review bottlenecks by automating the discovery of relevant records and the redaction of sensitive data,…
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…