My work focuses on foundation models for astronomy and astrophysics, with applications such as galaxy morphological classification and the classification of auroral emission spectra (RFIAP 2026), along with contributions to observational programs involving transient events.
I also contribute to the UniverseTBD collaboration, notably on AstroLLaVA, a vision-language model for astronomy. I am a member of the STAROS Projects team, which develops projects centered on spectroscopy for astronomy.
A complete list of my publications is available on ORCID and Google Scholar.
We examine whether Vision Transformer attention can serve as a built-in interpretability mechanism on ordered 1D scientific signals, where physical ground truth enables direct …
This study evaluates the performance of existing visual foundation models, based on ViT, SwinV2, BEiT or DINOv2, for astronomical applications, particularly galaxy morphological …
We present AstroLLaVA, a vision language model for astronomy that enables interaction with astronomical imagery through natural dialogue. By fine-tuning the LLaVA model on a …
Poster on classifying auroral emission spectra with a 1D Vision Transformer, whose attention maps recover known emission lines without spectroscopic priors.
Talk on evaluating and fine-tuning DINOv2 and other visual foundation models for galaxy morphological classification.
Poster on evaluating visual foundation models (ViT, DINOv2, CLIP) for astronomical tasks such as galaxy morphological classification.
ePoster — Session SS10: The impact of the rapidly evolving field of artificial intelligence on astrophysics research.
