BOOK OF ABSTRACTS AND CONTRIBUTED PAPERS: International scientific conference Meeting on Operational and Research Capabilities for Better Understanding Solar-Terrestrial Interactions ,
Pages: 53-54,
https://doi.org/10.69646/aob250918
International scientific conference Meeting on Operational and Research Capabilities for Better Understanding Solar-Terrestrial Interactions
Published by: Scientific Society Isaac Newton

Over the past decade, the Heliophysics community has increasingly explored machine learning (ML) techniques, as reflected in the exponential growth of peer -reviewed publications, conference presentations, and funding opportunities. Among the key areas of M L application, space weather forecasting stands out as a field with tremendous potential for data -driven decision -making. This contribution highlights some of the ongoing ML research efforts at Georgia State University, including: (1) ML -driven forecasting of solar transient events (STEs) such as solar flares, coronal mass ejections, and solar energetic particles; (2) intertwining the ML with physics -based simulations for further enhancement of predictions of STEs; (3) the development of ML -ready datasets a nd data exploration tools for improved forecasting of STEs, radiation exposures at aviation altitudes, and other applications.