Carlos J. Díaz Baso

Carlos J. Díaz Baso

Postdoc in Solar Physics

Oslo University, RoCS

About Me

Hello, and welcome! I am a Postdoctoral researcher scientist working in the Rosseland Centre for Solar Physics at Oslo University.

My general areas of interest are Bayesian statistics, Deep Learning and Solar Physics. My research focuses on understanding solar phenomena and their origin through the analysis of spectropolarimetric observations. Thanks for stopping by!

I also develop open interactive tools — try Solar SIR, a browser-based LTE spectral synthesis app built on the SIR inversion code.

News

  • [May 20, 2026] New preprint: Accelerating 3D Non-LTE Synthesis with Graph Neural Networks [arXiv] [project].
  • [May 15, 2026] New preprint: IRIS NUV diagnostics for Ellerman bombs: spectral properties, thermodynamics, and formation height [arXiv] [project].
  • [April 15, 2026] Accepted paper: Thermodynamic and magnetic evolution of an eruptive C-class solar flare observed with SST/TRIPPEL-SP [Journal] [arXiv] [project].
  • [February 20, 2026] Accepted paper: Active chromospheric fibril singularity: Coordinated observations from Solar Orbiter, SST, and IRIS [Journal] [arXiv] [project].
  • [February 10, 2026] New preprint: Inspectorch: Efficient rare event exploration in solar observations [arXiv] [project].

See all news →

Publications

Accelerating 3D Non-LTE Synthesis with Graph Neural Networks

Numerical modeling of 3D non-local thermodynamic equilibrium (non-LTE) radiative transfer is a significant computational bottleneck in …
A. Vicente Arévalo, A. Asensio Ramos, Carlos J. Díaz Baso
PDF ArXiv

IRIS NUV diagnostics for Ellerman bombs: spectral properties, thermodynamics, and formation height

We establish robust diagnostics for identifying Ellerman bombs (EBs) using Near-Ultraviolet (NUV) spectra from the Interface Region …
I. J. Soler Poquet, Carlos J. Díaz Baso, A. Sainz Dalda, L. H. M. Rouppe Van Der Voort, D. Nóbrega-Siverio, R. Joshi
PDF ArXiv

Thermodynamic and magnetic evolution of an eruptive C-class solar flare observed with SST/TRIPPEL-SP

We investigate the physical processes driving a C5.1-class solar flare and filament eruption in active region NOAA 12561 on July 7, …
Carlos J. Díaz Baso, J. De La Cruz Rodríguez, H.-P. Doerr, M. Van Noort, A. Prasad, A. Feller, D. Kiselman
PDF DOI Journal ArXiv

Active chromospheric fibril singularity: Coordinated observations from Solar Orbiter, SST, and IRIS

We report the discovery of a ‘chromospheric fibril singularity,’ a new feature observed in the solar chromosphere using …
Reetika Joshi, Luc Rouppe Van Der Voort, Guillaume Aulanier, Sanja Danilovic, Avijeet Prasad, Carlos J. Díaz Baso, Daniel Nóbrega-Siverio, Nicolas Poirier, Daniele Calchetti
PDF DOI Journal ArXiv

Inspectorch: Efficient rare event exploration in solar observations

We present Inspectorch, an open-source Python framework designed to efficiently identify rare and unusual events in large, …
Carlos J. Díaz Baso, I. J. Soler Poquet, C. Kuckein, M. Van Noort, N. Poirier
PDF Code ArXiv
See all publications

Recent Talks

Slides:

  • Advances in machine learning applications on photospheric and chromospheric studies, 45th COSPAR Scientific Assembly, Busan, South Korea, 13 - 21 July 2024 - Link
  • The Force Awakens: Unleashing Deep Learning in Solar Physics, Oslo AI Product Lab, Oslo, Norway, May 25, 2024 - Link
  • Deep Learning 2.0: Combining physics-based models with data-driven solutions, Lockheed Martin Solar and Astrophysics Laboratory (LMSAL), California, USA, May 16, 2024 - Link
  • Deep Learning 2.0: Combining physics-based models with data-driven solutions, Instituto de Astrofísica de Canarias (IAC), Tenerife, Spain, October 15, 2023 - Link
  • Deep Learning 2.0: Combining physics-based models with data-driven solutions, Leibniz-Institut für Sonnenphysik (KIS), Freiburg, Germany, June 5, 2023 - Link
  • The Potential of Machine Learning for Efficient Analysis of Solar Observations and simulations, ITA Colloquium 2023, Oslo, Norway, March 17, 2023 - Link
  • Differentiable programming for spectra modeling and inference, RoCMI 2023, Longyearbyen, Svalbard, February 26 - March 2, 2023 - Link
  • Unleashing the Potential of Machine Learning for Efficient Analysis of Solar Observations, Universitat de les Illes Balears, Spain, February 17, 2023 - Link
  • Application of machine learning and neural networks to data processing in solar physics, Solar Space Plasma seminar, National Astronomy Observatory of Japan, Tokyo, Japan, December 2, 2022 - Link
  • Unlocking the potential of deep learning for the analysis of spectropolarimetric observations, Solar Polarization Workshop 10 (SPW10), Kyoto, Japan, November 7-11, 2022 - Link
  • Application of machine learning and neural networks to data processing, Hinode-15 / IRIS-12, Czech Republic, Prague, September 19-23, 2022 - Link

Videos:

  • Stockholm University Seminar - 2021/10/15 - Link
  • HAO Colloquium - 2020/10/07 - Link

Thesis

Ph.D. Thesis: Analysis of the magnetic and dynamic structure of solar filaments, September 2018 [26.6MB]. Download

M.Sc. Thesis: Inversion techniques and their application to spectropolarimetric data of the solar photosphere and chromosphere, June 2015 [3.3MB]. Download

Fellowship Thesis: Inversion of spectropolarimetric data, June 2014 [1.8MB]. Download

B.Sc. Thesis: Introduction to solar spectropolarimetric data, June 2013 [1.8MB]. Download

Experience

 
 
 
 
 

Postdoctoral researcher

Rosseland Centre for Solar Physics, RoCS

Oct 2022 – Present Oslo, Norway
 
 
 
 
 

Postdoctoral researcher

Institute for solar physics, ISP

Oct 2018 – Sep 2022 Stockholm, Sweden
 
 
 
 
 

PhD in Astrophysics

Universidad de La Laguna

Oct 2014 – Sep 2018 Tenerife, Spain
 
 
 
 
 

Master in Astrophysics

Universidad de La Laguna

Oct 2013 – Jun 2015 Tenerife, Spain
 
 
 
 
 

Degree in Physics

Universidad de La Laguna

Jun 2013 – Sep 2009 Tenerife, Spain

Contact

  • carloskdb@gmail.com | carlos.diaz@astro.uio.no