Summary
Jorge Gallo is a postdoctoral researcher in theoretical particle physics with eight years of experience probing flavour physics, B-meson anomalies, effective field theories, axion-like particles and ML-driven phenomenology. Currently based at the Università di Padova after a PhD and research stint at Universidad de Zaragoza, he has authored multiple peer-reviewed studies linking machine learning techniques to concrete flavour-physics analyses. He teaches undergraduate physics courses and has co-supervised bachelor theses, bringing clear communication and mentorship to complex topics. Jorge’s work combines formal EFT approaches with phenomenological model-building and data-driven methods, reflecting a rare mix of analytical rigor and computational experimentation in the study of beyond-Standard-Model signatures.
8 years of coding experience
Doctor of Philosophy (PhD), Physics, Doctor of Philosophy (PhD), Physics at Universidad de Zaragoza
Máster, Física Teórica, Máster, Física Teórica at Universidad Complutense de Madrid
English, French, German, Spanish, Italian