GSST/CBERS-5 International Symposium on Machine Learning in Heliophysics and Space Weather

Using Machine Learning to Understand the Impact of Space Weather on Exoplanets

Aug 20, 2026, 4:10 PM

1h 20m

Fernando de Mendonça - LIT (National Institute for Space Research, São José dos Campos, SP, Brazil)

Poster Machine Learning in Space, Earth & Atmospheric Sciences Poster Session

Speaker

Salma Makhtich (Faculte of Science Semlalia Marrakech Morocco)

Description

Space weather, caused by stellar activity such as flares and stellar winds, can strongly affect the atmospheres of exoplanets. These effects are important for understanding whether a planet can keep its atmosphere and potentially support life.
In this work, we present a simple theoretical overview of how machine learning can help study these effects. We explain how variations in stellar activity can influence exoplanet atmospheres and how machine learning can be used to find patterns between them.
The goal is not to build a model, but to show how artificial intelligence could be used as a tool to better understand complex interactions between stars and planets.
This study provides an accessible introduction to the connection between space weather, exoplanets, and machine learning, and highlights the importance of combining physics with modern data analysis methods.