OCO2/3 Bad Pixel Map
A machine learning approach is developed to improve the bad pixel map that masks damaged or unusable pixels in the imaging spectrometers of the Orbiting Carbon Observatory-2 and -…
SpecTF Clouding Screening for Imaging Spectroscopy
A deep learning model for accurate, data-driven cloud detection in imaging spectroscopy data.
Decision Theoretic Planning
Algorithms to plan and optimize different outcomes
Cloud avoidance for Atmospheric Retrieval Missions
Methods for atmospheric retrieval of earth science data.
Dynamic, Intelligent, Tomographic Imaging
Methods for analyzing 3D imaging data
Adversarial Policy Evolution via AI
Develop and improve decision-making strategies by having them compete against adversaries, learning and evolving through repeated challenges.
Adaptive Problem Solving / Hyperparameter Optimization
Adaptable algorithms to analyze hyperspectral data
Onboard Science Instrument Autonomy (OSIA) for OWLS
Onboard biosignature detection for a suite of life-detection instruments (motility, fluorescence, metabolism indicators) and summarizing the data to overcome bandwidth constraints…
EMIT Methane Plume Detection
Machine learning based detection of methane plumes from imaging spectroscopy data.
Science Autonomy for NEAScout
Autonomy software to support on board AI science capabilities for the Near Earth Asteroid Scout Mission.
Time Series Forecasting, Evaluation and Deployment (Time-FED)
Time-FED is a machine learning system for Time series Forecasting, Evaluation and Deployment. TimeFED was created in response to the following data realities: 1) data contains si…
AI Risk-aware task and motion planning for snake-like robots in icy enviroments
Enables task and navigation planning inextreme ice terrains/environments.
The AQcGAN Air Quality Emulator for GEOS
AQcGAN is an air quality emulator for surface O3 and NOx concentrations.
The AIMFAHR Project
Artificial Intelligence (AI) techniques, particularly Machine Learning (ML), have undergone significant growth in heliophysics research in recent years. Various ML models have eme…
Qualitative Evaluation of Foundation Models (QEFM)
Objective: Quantify the performance of Foundation Models (FMs) for weather and climate to guide GSFC scientists in effectively integrating AI into their research.
System for Uncertainty, Risk, and Feature Assessment of Surfaces (SURFAS) Holistic Scene Analysis
SURFAS, given the above combination of inputs for a particular vehicle, is informed by expertise of mission designers to fuse relevant data together in order to create a holistic…
Explainable Machine Learning Methods for Ocean Worlds Mass Spectrometry Data: Biosignatures and Environmental Characterization
Future astrobiological and geochemical investigations of ocean worlds (OWs) such as Europa and Enceladus will face challenges that can be addressed through science autonomy. While…
Transiting Exoplanet Survey Satellite (TESS) Neural Network (NN)
The Transiting Exoplanet Survey Satellite (TESS) is a NASA mission focused on exploring and finding exoplanets around nearby stars using the transiting method. TESS telescope cove…
RAG Chatbots: Enhancing User and Internal Support Through Dual Knowledge Systems
This work presents two complementary RAG-based chatbot systems developed for NASA's Community Coordinated Modeling Center. These tools represent practical applications of retriev…
Machine Learning Techniques for Fast Radiative Transfer
Radiative transfer models for satellite data assimilation and physical atmospheric retrievals need to be both fast and accurate to fulfill operational constraints. These contradic…
Using ChatGSFC to Streamline Analysis and Reporting
A series of 90+ examples of how ChatGSFC or a NASA-focused LLM can be utilized to enhance project planning and controls (PP&C) analysis and streamline project management activitie…
Ground-based Detection of Martian Dust Devils With a Fine-tuned Fast R-CNN
We developed a two-stage pipeline for efficient dust devil detection in Mars rover imagery. Our approach combines preprocessing filters to remove unsuitable images, followed by a…
A Detection and Reporting System for Spacecraft Threats
Goal is to identify, and potentially predict when an event (e.g., anomaly, interference, etc.) has/will occur. Spacecraft anomalies / interference events can take them out of of m…
Neural Posterior Estimation for X-ray reflection spectroscopy: Training on complex physical models and AGN Observation-Driven Parameter Grids.
The development of an automated inference tool tailored to extract key physical parameters from obscured AGN (active galactic nuclei) X-ray spectra by means of more complex physic…