75 citations · 97 across the 15 of their papers we have counts for
17 papers
SWAN-SF-V2: A Multivariate Time Series Dataset for Space Weather Data Analytics; Now with AIA and Weighted SHARP Parameters
Dustin Kempton, Griffin Goodwin, Reet Gupta +4
Since its original publication in 2020, the SWAN-SF dataset has been cited in over 300 research publications. Here we describe a comprehensive update to the original multivariate t…
Neural Operator based Multi-Field Reconstruction of Inner Solar Boundary State
Vignesh Kumar Pandian Sathia, Reza Mansouri, Dustin J. Kempton +2
The Solar wind is a continuous flow of charged particles emanating from the solar surface and governed by complex, interacting magnetohydrodynamic processes. Accurate specification…
Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations
Rimsha Hameed Syeda, Dustin Kempton, Viacheslav Sadykov +2
Numerical modeling of solar plasma dynamics is affected by the resolution of the computational grid. This often requires the estimation of subgrid processes related to the small-sc…
Cluster-Weighted Training of Deep Surrogate Models for Subgrid Turbulent Transport
Rimsha Hameed Syeda, Dustin Kempton, Viacheslav Sadykov +2
Turbulence in the solar interior and atmosphere plays a crucial role in energy transport, yet modeling its subgrid-scale effects remains a major challenge. This study leverages mac…
Describing the swdatatoolkit: A Space Weather Data Analysis Library
Dustin Kempton, Griffin Goodwin, Tarun Kumar Reddy Thippareddy +3
swdatatoolkit is a Python-based scientific software library designed to support the acquisition, preprocessing, and analysis of solar and space weather data. The toolkit consolidat…
Toward Data-Driven Surrogates of the Solar Wind with Spherical Fourier Neural Operator
Reza Mansouri, Dustin Kempton, Pete Riley +1
The solar wind, a continuous stream of charged particles from the Sun's corona, shapes the heliosphere and impacts space systems near Earth. Variations such as high-speed streams a…
Autoregressive Surrogate Modeling of the Solar Wind with Spherical Fourier Neural Operator
Reza Mansouri, Dustin Kempton, Pete Riley +1
The solar wind, a continuous outflow of charged particles from the Sun's corona, shapes the heliosphere and impacts space systems near Earth. Accurate prediction of features such a…
Operational and Exploration Requirements and Research Capabilities for SEP Environment Monitoring and Forecasting
Viacheslav Sadykov, Petrus Martens, Dustin Kempton +15
Mitigating risks posed by solar energetic particles (SEPs) to operations and exploration in space and Earth's atmosphere motivates the development of advanced, synergistic approach…
FFAD: A Novel Metric for Assessing Generated Time Series Data Utilizing Fourier Transform and Auto-encoder
Yang Chen, Dustin J. Kempton, Rafal A. Angryk
The success of deep learning-based generative models in producing realistic images, videos, and audios has led to a crucial consideration: how to effectively assess the quality of…
Revisiting the Solar Research Cyberinfrastructure Needs: A White Paper of Findings and Recommendations
Gelu Nita, Azim Ahmadzadeh, Serena Criscuoli +15
Solar and Heliosphere physics are areas of remarkable data-driven discoveries. Recent advances in high-cadence, high-resolution multiwavelength observations, growing amounts of dat…
Multiscale IoU: A Metric for Evaluation of Salient Object Detection with Fine Structures
Azim Ahmadzadeh, Dustin J. Kempton, Yang Chen +1
General-purpose object-detection algorithms often dismiss the fine structure of detected objects. This can be traced back to how their proposed regions are evaluated. Our goal is t…
Towards Synthetic Multivariate Time Series Generation for Flare Forecasting
Yang Chen, Dustin J. Kempton, Azim Ahmadzadeh +1
One of the limiting factors in training data-driven, rare-event prediction algorithms is the scarcity of the events of interest resulting in an extreme imbalance in the data. There…
How to Train Your Flare Prediction Model: Revisiting Robust Sampling of Rare Events
Azim Ahmadzadeh, Berkay Aydin, Manolis K. Georgoulis +3
We present a case study of solar flare forecasting by means of metadata feature time series, by treating it as a prominent class-imbalance and temporally coherent problem. Taking f…
Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations
Gelu Nita, Manolis Georgoulis, Irina Kitiashvili +38
The authors of this white paper met on 16-17 January 2020 at the New Jersey Institute of Technology, Newark, NJ, for a 2-day workshop that brought together a group of heliophysicis…
Toward Filament Segmentation Using Deep Neural Networks
Azim Ahmadzadeh, Sushant S. Mahajan, Dustin J. Kempton +2
We use a well-known deep neural network framework, called Mask R-CNN, for identification of solar filaments in full-disk H-alpha images from Big Bear Solar Observatory (BBSO). The…
Challenges with Extreme Class-Imbalance and Temporal Coherence: A Study on Solar Flare Data
Azim Ahmadzadeh, Maxwell Hostetter, Berkay Aydin +4
In analyses of rare-events, regardless of the domain of application, class-imbalance issue is intrinsic. Although the challenges are known to data experts, their explicit impact on…
A Curated Image Parameter Dataset from Solar Dynamics Observatory Mission
Azim Ahmadzadeh, Dustin J. Kempton, Rafal A. Angryk
We provide a large image parameter dataset extracted from the Solar Dynamics Observatory (SDO) mission's AIA instrument, for the period of January 2011 through the current date, wi…