

SCIENTIFIC PRODUCTION
I. PUBLICATIONS AUTHOR Classification of HI Galaxy Profiles Using Unsupervised Learning and Convolutional Neural Networks: A Comparative Analysis and Methodological Cases of Studies Jaimes, G. 14th Astronomical Data Analysis Software and Systems (ADASS), 1 Jan 2025. Hydrogen, the most abundant element in the universe, is crucial for understanding galaxy formation and evolution. The 21 cm neutral atomic hydrogen (HI) spectral line maps the gas kinematics within galaxies, provi




















