Main Research Fields

My research field has varied over the years through different experiences, primarily focusing on observational cosmology and high-energy astrophysics.

Currently, I am researching AGN and galaxy cluster simulations using deep learning-based machine learning classification models within the scope of the XXL and Heritage FornaX projects. My role involves generating realistic low-count-rate XMM-Newton AGN and galaxy cluster simulations. The aim is to support the XXL survey in building an extensive galaxy cluster catalog to investigate large-scale structure formation and conduct cosmological studies of the Universe.

I completed my university studies with a master’s degree in observational cosmology, specializing in the use of Type Ia Supernovae to study dark energy. I evaluated the 4MOST instrument (on the VISTA telescope) for the TiDES survey, assessing its potential to improve cosmological parameter measurements, whilst using the Patheon+ data sample for comparison. Additionally, I complemented my research by exploring theoretical models of dark energy, determining whether experimental data from the Euclid and Roman missions could distinguish between these models. In my high-energy astrophysics research experiences, I focused particularly on the radio-loud quasar 4C74.26, analyzing its spin using data from NuSTAR and XMM-Newton.