Dr. Carlos José Díaz Baso earned his PhD in Astrophysics from the University of La Laguna in 2018. He is currently Head Engineer (researcher) at RoCS (Rosseland Centre for Solar Physics, University of Oslo) and was awarded a Ramón y Cajal Fellowship at the IAC in 2026. His main research interests include Bayesian statistics, deep learning, and solar physics. He is a member of the data modelling team of NASA’s MUSE mission, where he is one of the main contributors to its spectral disambiguation pipeline and, since 2026, leads this work within the Norwegian ESA-PRODEX contribution. His work focuses on understanding solar chromospheric phenomena (ranging from quiescent solar filaments to explosive events) and their magnetic origins.

 

To achieve this, he aims to analyze high-quality spectropolarimetric observations from both ground- and space-based instruments using innovative deep learning techniques and Bayesian inference, comparing these with numerical models of the solar atmosphere. Dr. Díaz Baso maintains a close collaboration with Dr. Asensio Ramos’s research team at the IAC. This team has pioneered advancements in spectropolarimetric inversions, the improvement of atmospheric aberration corrections, and the recovery of polarization signals in low signal-to-noise scenarios. Together, they have developed a research line focused on enhancing the capacity and precision of current methods to accelerate the analysis of observational data, including a radiative transfer emulator that speeds up spectral synthesis by orders of magnitude.

 

In this collaborative effort, the aim is to combine the complementary expertise of both researchers. Dr. Asensio Ramos will contribute radiative transfer models and technical expertise in implementing deep learning frameworks, while Dr. Díaz Baso will provide his experience with amortized Bayesian models, physics-informed neural fields and Bifrost MHD models to validate the accuracy of the results.