SABID 2026 workshop solicits high-quality original research papers in the closely related areas of solar and stellar astronomy big data. Innovative data mining techniques in these fields are poised to address open research questions ranging from solar weather predictability to our place in the Universe. The topics include, but are not limited to, the following:
Managing the Flood of Solar & Stellar Astronomy Big Data: Computational models, quality evaluation, scientific standards, system architectures, cloud management, and heterogeneous data integration.
Solar & Stellar Data Science, Informatics and Statistics: Search models, recognition algorithms, architecture efficiency, visualization, astrostatistics, hyperspectral imaging, high-velocity mining, image processing, multi-structured mining, and novel algorithms.
Applications related to Solar Astronomy Big Data Mining: Space weather, case studies, project experiences, crowdsourced research, and social web distribution.
Enhancing the Solar-Stellar Connection with Big Data: helio/asteroseismology, Sun-like star surveys, event identification, and dynamo modeling.
Deep Learning and Neural Network Architectures for Solar & Stellar Data: DNNs, Transformers, Vision Transformers (ViTs), and attention mechanisms.
Explainable and Trustworthy AI for Astronomy: Explainable AI (XAI), interpretable machine learning, uncertainty quantification, saliency analysis, counterfactual explanations, and trustworthy forecasting systems.
Multimodal and Multi-spacecraft Learning: Fusion of imagery, magnetograms, spectra, particle fluxes, and time-series observations from heterogeneous solar and stellar instruments.
Physics-Informed and Scientific Machine Learning: Hybrid physics-AI models, physics-guided neural networks, and data-driven discovery in heliophysics and stellar astronomy.
Scalable AI Infrastructure for Astronomy Big Data: High-performance computing (HPC), distributed learning, edge/cloud AI systems, and efficient training pipelines for large-scale scientific datasets.
Bo Shen (New Jersey Institute of Technology)
Rafal Angryk (Georgia State University)
Viacheslav Sadykov (Georgia State University)
Soukaina Filali Boubrahimi (Utah State University)
Petrus Martens (Georgia State University)