Application of machine learning algorithms in the context of astroparticle physics and photonics

• Development of deep-learning-based event reconstruction algorithms for gamma-ray observatories (graph networks, attention-based architectures, and convolutional neural networks)
• Development of machine-learning and deep-learning-based classifiers for background rejection
• Analysis of stereoscopic observation data (multi-view image reconstruction)
• Acceleration of air shower simulations using deep generative models
• Application of clustering algorithms to gamma-ray data
• Anomaly detection using deep learning