PhD candidate in Astrophysics at UNAM and the University of Groningen, specializing in cosmology, gravitational lensing, and deep learning. Passionate about applying artificial intelligence to extract cosmological information from large-scale surveys. Member of the LSST and Euclid collaborations.
Download CV (PDF)Instructor for Atomic Physics, Nuclear & Subnuclear Physics, and Analytical Mechanics (2023–2024).
Development of generative models and simulation-based inference for gravitational lensing analysis. Collaboration with LSST and Euclid missions.
Used Physics-Informed Neural Networks to model astrophysical systems. Published in UNAM Summer School proceedings.
Co-authored a peer-reviewed paper on neural networks for cosmology; foundation for future research in AI and astrophysics.
Research in gravitational lensing and deep learning inference techniques. Supervisors: Dr. J.A. de Diego, Dr. L. Koopmans.
Thesis on Physics-Informed Neural Networks applied to cosmological systems.
Thesis: Observational Cosmology with Artificial Neural Networks.
I enjoy exploring artificial intelligence applications in space science, gravitational lensing, and cosmological inference.
Outside research, I’m passionate about teaching, open-source collaboration, and scientific outreach in astrophysics and machine learning.