Rion Glenn Nazareth

Currently, I am working on probing the impact of relativistic particles on galactic outflows and the thermal and non-thermal observational signatures of feedback in bright AGN. In particular, I am interested in understanding the observed link between AGN obscuration and radio emission. Stay tuned for updates!

Many spiral galaxies host magnetic fields with energy densities comparable to those of the turbulent and thermal motions of their interstellar gas. These magnetic fields confine cosmic rays and affect the structure and dynamics of the interstellar medium. We developed a new framework that uses observable quantities as input: the galaxy rotation curve, the surface densities of the gas, stars and star formation rate, and the gas temperature. Our results show that the scaling relation predictions of our model are in good agreement with the observed galaxy properties, and the inferred free-parameter values are remarkably consistent across the four nearby galaxies to which we apply the model.

During my master's research, I developed machine learning models to identify and predict linear geological features (lineaments) on Europa's surface — a crucial step in searching for potential biosignatures in spectral data from these regions. I trained multiple models using datasets created with different annotation techniques and proposed a novel hybrid approach that combines convolutional neural networks with random forest algorithms.