I am currently an MSc researcher in Astronomy and Astrophysics, with a particular interest in applying machine learning and data driven methods to astronomical problems.

A significant part of my research focuses on studying galaxies using large photometric datasets. I apply machine learning to the morphological and activity based classification of galaxies, as well as to the estimation of fundamental galaxy parameters from photometric information. Through this work, I am interested in developing scalable and reliable approaches that can be applied to data from different astronomical surveys.

In addition, I contribute to an international research project investigating the interstellar medium of the M33 Galaxy. As part of this work, I use spatial and spectroscopic information from MUSE observations to investigate the physical properties of ionised gas and its surrounding environment within the galaxy.

My broader research interests include extragalactic astronomy, active galaxies, astronomical surveys, the interstellar medium, and astrostatistics. Overall, my work lies at the intersection of astronomy, machine learning, and large scale data analysis.

I am a member of the Royal Astronomical Society and participate in the Rubin Observatory LSST science community, including the Galaxies and AGN Science Collaborations.