Career & Research Focus

I am a postdoctoral researcher specialized in the use of machine and deep learning techniques for the exploitation of large astronomical datasets. I hold a PhD in Astrophysics from the Universidad Complutense de Madrid (Spain) and currently work at the Centro de Astrobiología (CAB) as a postdoctoral researcher for the European Space Agency (ESA).

My research focuses on three main areas:

• Detailed visual morphology of galaxies in the Euclid mission: Using visual morphology classifications, obtained with the Zoobot deep foundation model, I am leading a project to study the effects of environment on different galaxy morphologies in high density environments. In particular, I am studying the effect of environmental processes in galaxy clusters on detailed morphological features, such as stellar bars.
• M dwarfs and ultracool dwarfs parameter determination: I developed a deep transfer learning approach using autoencoder neural networks to estimate atmospheric parameters (effective temperature, surface gravity, metallicity, and rotational velocity) of M dwarfs from high-resolution CARMENES spectra, bridging the gap between synthetic models and observed data. I further applied the same methodology to low-resolution spectroscopy to determine the effective temperature of ultracool dwarfs in the Euclid mission.
• Identification and characterisation of low-mass objects: This line of research focuses on the development of Virtual Observatory methodologies to efficiently identify ultracool dwarf candidates in wide-field photometric surveys.

In summary, my research explores how data-driven approaches, combining Virtual Observatory infrastructure with artificial intelligence, can transform astronomical research by enabling the automated analysis of vast datasets from current and future surveys.