Correcting NASA NPOL weather radar beam blockage using machine learning approaches
Our objective is to fill in blocked radar data using Convolutional Neural Networks (CNN). This project is in the early stages in preparing the data and model for training.
Application of ML to Detection of Anomalies in Spacecraft Health and Status Data
We are collaborating with the Magnetospheric Multiscale (MMS) mission to research Machine Learning (ML) techniques capable of predicting and detecting anomalies in spacecraft heal…
AI: Logic Design and Verification
There has been much discussion on the use of Artificial Intelligence (AI) in many fields. This study is a first look at the use of AI in the field of digital electronics, primari…
SOLARIS-AI: Analyze Planetary Modulation in Solar Activity Cycles (Prediction of solar storms possible?)
This AI-driven project analyzes multi-decadal solar activity datasets to identify and quantify periodic signals that correlate with planetary orbital mechanics. The project proces…
Specifying Properties Of Dayside Magnetopause Reconnection From A Machine-Learning Model For The Earth'S Cusps
Implementation of models of the magnetospheric CUSP using in-situ ion flux data from ESA's Cluster mission and DMSP spacecraft. The models produce 3-D ion flux distributions in re…
Strategic Text Augmentation & Research Synthesis for Physics Innovation Narratives & Evaluations"
This project is an AI-assisted daily workflow solution designed to streamline the scientific documentation process for physics researchers. The system leverages ChatGSFC's advance…
AI Based VoIP Outage Prevention
This project is to collect the live data from Voice Over Internet Protocol (VoIP) currently resides in NASA network. Then to apply an appropriate Machine Learning technique to lea…
Quantification of Uncertainty Analysis Toolkit (QUAnT)
The Quantification of Uncertainty Analysis Toolkit (QUAnT) is a digital-twin framework that informs and guides the design process of complex, large-scale, multidisciplinary system…
Machine Learning effort to calculate Parker Solar Probe magnetometer offsets
Testing various ML algorithms to model the magnetometer offset values at points in the orbit where the traditional methods are not available.
Identifying global dust and smoke over ocean using MODIS sensor
Using ML RF/CNN to detect dust in MODIS images.
A Forecasting Scheme For Accelerated Harmful Algal Bloom Monitoring (FASTHAB)
To develop an AI/ML forecast water quality model initial targeted for the Chesapeake bay.
Instantaneous photosynthetically available radiation models for ocean waters using neural networks
Neural network forward models were developed to predict subsurface vertical profile of instantaneous photosynthetically available radiation (IPAR) for both open ocean and coastal…
Space Grade Linux
Current methodologies to deploy edge AI on spacecraft face a critical cost barrier due in part by reliance on traditional real-time operating systems. The solution lies in adoptin…
Integrating Explainable Machine Learning with Physics for Enhanced Wildfire Detection in Observation-Constrained Environments
Satellite-based fire detection provides critical data for fire management, fire spread modeling, air quality forecasts, and assessments of fire impacts on ecosystems and communiti…
The airborne Compact Fire Imager (CFI) for measurements across the entire fire lifecycle
CFI is a new pushbroom instrument with six spectral bands between the shortwave infrared (SWIR) and thermal infrared (TIR), including two channels in the mid-wave infrared (MWIR)…
Natural Language query processor for Common Metadata Repository
A chatgpt-like prompt query interface that uses large language models to extract intent from chat query to determine spatial, temporal and science variable filters. These filters…
PIX4DCloud
Geostationary spectrometer based foundation model (ABI-FM) and evaluation on benefits for 3D cloud and convection related downstream tasks
Lunar Foundation Model
Funded by the Office of the Chief Science Data Officer, the Lunar Foundation Model (LFM) is a joint effort between GSFC, MSFC, and IBM that will harness a large and diverse array…
MADI - Modular AI for Design and Innovation
MADI (Modular AI for Design and Innovation) is a decentralized, open-source AI platform that identifies unexplored research "whitespace" between scientific disciplines through sec…
Developing an ML-based subcolumn generator
ML generator for cloudy and precipitating subcolumns to be used in global climate models.
CHESS: Coronal Hole Extraction with Semantic Segmentation
This project aims at expanding the training of two Convolutional Neural Networks (CNNs) that we have already developed to obtain a more efficient, more accurate, and least-biased…
Machine learning for X-ray astronomical spectroscopy
We use Simulation Based Inference to construct 34000 artificial spectra that are representative of observed Active Galactic Nuclei X-ray spectra with NASA's NuSTAR X-ray telescope…
Using MML code generation to create new high-energy astrophysics science software
We plan to train an LLM on previous large code bases for high-energy astrophysics science pipeline and analysis software. HEASARC is under a mandate to work on next-generation sc…
Diffusion Modeling of the Solar Corona
Diffusion models such as DeepMind’s GenCast have demonstrated powerful performance in terrestrial weather forecasting, achieving results on-par and surpassing leading medium-range…