HelioPhysics

2025

CIPHER: Scalable Time Series Analysis for Physical Sciences with Application to Solar Wind Phenomena - Neurips 2025, Paper Arxiv

Uncovering Solar Wind Phenomena with iSAX, HDBSCAN, Human-in-the-loop and PSP Observations - Neurips 2025, AGU 2025, Paper Arxiv

Scalable Machine Learning Analysis of Parker Solar Probe Solar Wind Data - Neurips 2025, Paper Arxiv

Corona-Fields: Leveraging Foundation Models for Classification of Solar Wind Phenomena - Paper Arxiv,  AAAI Workshop

FOXES: A Framework For Operational X-ray Emission Synthesis - Neurips 2025, AGU 2025, Paper Arxiv

Forecasting the Ionosphere from Sparse GNSS Data with Temporal-Fusion Transformers - Neurips 2025, Paper Arxiv

Image calibration between the Extreme Ultraviolet Imagers on Solar Orbiter and the Solar Dynamics Observatory, Astronomy & Astrophysics - Paper Arxiv

Data-Driven Solar Surface Flux Transport Modeling with Uncertainty Quantification - Neurips 2025

Estimating high resolution photospheric flows using an AI surface flux transport model - AGU 2025

An AI-powered Surface Flux Transport model to measure high-resolution velocity fields and forecast magnetic flux emergence - AGU 2025

Parker Solar Probe Machine Learning Ready Dataset - AGU 2025

Masked Autoencoders and Neural Fields for Solar Wind Structure Classification from SDO Observations - AGU 2025

Understanding the relationships of PSP Solar Wind Parameters with Distributed Computation using Dask and Deep Learning techniques - AGU 2025
Solar Wind Structure Decipher Clustering Using iSAX-pipeline Composed of iSAX Compression, and HDBSCAN - AGU 2025

SDO-ML Video Foundation Model with Neural Fields and its application to Solar Wind Structure classification -  AGU 2025

IonCast: a Deep Learning Framework for Forecasting Ionospheric Dynamics - Neurips 2025, AGU 2025

Connecting the Dots: a Machine Learning Ready Dataset for Ionospheric Forecasting Models - Neurips 2025, AGU 2025

Reasoning With a Star: A Heliophysics Dataset and Benchmark for Agentic Scientific Reasoning - Neurips 2025

An Agentic Orchestration System for Heliophysics Tasks - Neurips 2025

2024

Instrument-To-Instrument translation: Instrumental advances drive restoration of solar observation series via deep learning - Nature Communications DOI: 10.21203/rs.3.rs-1021940/v1

Improving Thermospheric Density Predictions in Low-Earth Orbit With Machine Learning - AGU Space Weather Volume 22, Issue 2
DOI 10.1029/2023SW003652

SDO-FM is building a foundation model (FM) using Solar Dynamics Observatory (SDO) data, Software for the NASA Science Mission Directorate Workshop 2024

Instrument-to-Instrument translation: An AI tool to intercalibrate, enhance and super-resolve solar observations, EGU General Assembly 2024 
DOI: 10.5194/egusphere-egu24-15813

Instrument to Instrument (ITI) Translation, NASA AI Conference 2024

Spectral Irradiance of the 3D Sun on Mars, European Space Weather Week 2024 (FDL-X Heliolab 2024)

ITI: An Instrument-to-Instrument translation tool for Heliophysics and Earth science, AGU 2024

How Heliolab’s commitment to Open Science is creating a critical mass of new AI capabilities - AGU 2024

Deep Learning image burst stacking to reconstruct high-resolution ground-based solar observations, 17th European Solar Physics Meeting ESPM-17

Machine learning discovery of cost-efficient dry cooler designs for concentrated solar power plants - paper, Nature Journal
DOI 10.1038/s41598-024-67346-6

SuNeRF: 3D Reconstruction of the Solar EUV Corona Using Neural Radiance Fields - Astrophysical Journal Letters (FDL USA 2022),
DOI 10.3847/2041-8213/ad12d2, Arxiv 2401.16388

Physically Motivated Deep Learning to Superresolve and Cross Calibrate Solar Magnetograms - The Astrophysical Journal, DOI 10.3847/1538-4365/ad12c2

Virtual EVE: a Deep Learning Model for Solar Irradiance Prediction - Paper Arxiv 2408.17430v1

Multiscale Geoeffectiveness Forecasting using SHEATH and DAGGER - Poster, Astronomical Society of India 2024

New Insights into Coronal Physics from EUV and UV Spectroscopy - AGU 2024

MEGS-AI an AI model to estimate the full EUV spectrum using AIA images - AGU 2024

Prediction of Solar Transient Events Using Machine Learning - AGU 2024

Artificial Intelligence (AI) for scientific discovery in solar wind and Earth interaction - AGU 2024

2023
A Scientific Cloud Computing Platform for Ingestion and Processing of SDO Data - 4th Eddy Cross-Disciplinary Symposium (FDL-X 2023)

Leveraging Artificial Intelligence to Enhance the Science Return of 4𝛑 Solar Constellations - Paper, Bulletin of the AAS Vol 55, Issue 3 2023 (FDL-X 2022) DOI: 10.3847/25c2cfeb.aa5f09f6

AIA is All You Need: SDO MEGS A&B virtualization via Convolutional Deep Learning - 4th Eddy Cross-Disciplinary Symposium (FDL-X 2023)

A Novel Synthesis of SDO EVE MEGS A&B Spectral Irradiance Data through Convolutional Deep Learning - AGU 2023 (FDL-X 2023)

A Scientific Cloud Computing Platform for Ingestion and Processing of SDO Data - DASH 2023 (FDL-X 2023)

Virtual EVE: a Deep Learning Model for Solar Irradiance Prediction - NeurIPS 2023 (FDL-X 2023)

AI Inference Products, Foundation Models and multi-domain approaches to NASA Heliophysics - 4th Eddy Cross-Disciplinary Symposium (FDL-X Helio)

Multiscale Geoeffectiveness Forecasting using SHEATH and DAGGER- 4th Eddy Cross-Disciplinary Symposium (FDL-X 2023)

Improving thermospheric drag modeling with EUV images: an FDL-X 2023 project - 4th Eddy Cross-Disciplinary Symposium (FDL-X 2023)

High-Cadence Thermospheric Density Estimation enabled by Machine Learning on Solar Imagery - NeurIPS 2023 (FDL-X 2023)

Karman - a Machine Learning Software Package for Benchmarking Thermospheric Density Models - AMOS 2023 (FDL-X 2023)

A Federated Distributed Learning Benchmark for Solar Wind Speed Forecasting Using Solar EUV Images - Space Weather Workshop 2023 (FDLUSA 2022)

2022

Global Geomagnetic Perturbation Forecasting Using Deep Learning - AGU Space Weather Volume 20, Issue 6 DOI 10.1029/2022SW003045 Arxiv 2205.12734v1

2021

Modeling and forecasting ground geomagnetic perturbations using deep learning on spherical harmonics - COSPAR2021 Machine Learning for Space Sciences (You Tube Link)  (FDL USA 2020)

Multichannel autocalibration for the Atmospheric Imaging Assembly using machine learning - Astronomy & Astrophysics Journal (FDL USA 2019)
DOI 10.1051/0004-6361/202040051 Arxiv 2012.14023v4

Auto-Calibration and High-Fidelity Virtual Observations of Remote Sensing Solar Telescopes with Deep Learning - JPL AI and Data Science Workshop 2021 (FDL USA 2019) [I]

Correlation of Auroral Dynamics and GNSS Scintillation with an Autoencoder - JPL AI and Data Science Workshop 2021 (FDL USA 2019) [I]

Autonomous deep-space missions: can deep learning be used to optimize data transmission - COSPAR 2021 (FDL USA 2019)

Automating the Calibration of the Atmospheric Imaging Assembly - COSPAR 2021 (FDL USA 2019)

Forecasting Ground Magnetic Perturbation Using Deep Learning on Spherical Harmonics - American Meteorological Society 101th annual meeting 2021 (FDL USA 2020)

2020

Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning - Paper at AGU 2020 (FDL USA 2019)

Determining new representations of “Geoeffectiveness” using deep learning - AGU 2020 (FDL USA 2020)

Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly instrument with Deep Learning- AGU 2020 (FDL USA 2019)

RotNet: Fast and Scalable Estimation of StellarRotation Periods Using Convolutional NeuralNetworks - NeurIPS 2020 ML4PS (Physical Sciences) Workshop (FDL USA 2020)

Global Earth Magnetic Field Modeling and Forecasting with Spherical Harmonics Decomposition - NeurIPS 2020 ML4PS (Physical Sciences) Workshop  (FDL USA 2020)

2019

Using U-Nets to create high-fidelity virtual observations of the solar corona - NeurIPS Workshop 2019 (FDL USA 2019)
Arxiv 1911.04006v1

A deep-learning based approach for predicting high latitude ionospheric scintillations using geospace data and auroral imagery - JPL NASA Abstract (FDL USA 2019)

Auto-Calibration of Remote Sensing Solar Telescopes with Deep Learning- NeurIPS Workshop 2019 (FDL USA 2019) Arxiv 1911.04008v1

Single-Frame Super-Resolution of Solar Magnetograms: Investigating Physics-Based Metrics & Losses - NeurIPS Workshop 2019 (FDL USA 2019)
Arxiv 1911.01490v1

Correlation of Auroral Dynamics and GNSS Scintillation with an Autoencoder - NeurIPS Workshop 2019 (FDL USA 2019)
Arxiv 1910.03085v1

Prediction of GNSS Phase Scintillations: A Machine Learning Approach - NeurIPS Workshop 2019 (FDL USA 2019)
Arxiv 1910.01570v1

A deep learning Approach to forecast Tomorrow's Solar Wind Parameters- AGU 2019 (FDL USA 2019)

Enhancing the Predictability of GNSS Scintillations - AGU 2019 (FDL USA 2019) [I]

Auto-calibration and reconstruction of SDO’s Atmospheric Imaging Assembly channels with Deep Learning- AGU 2019 (FDL USA 2019)

A deep learning virtual instrument for monitoring extreme UV solar spectral irradiance - Science Advances 2019 (FDL USA 2018)
DOI 10.1126/sciadv.aaw6548

A machine learning dataset prepared for NASA’s Solar Dynamics Observatory- Astrophysical Journal 2019 (FDL USA 2018)
DOI 10.3847/1538-4365/ab1005 Arxiv 1903.04538v1