Artificial Intelligence and Advanced Inference (IA2)
Instituto de Astrofísica de Canarias
About
The IA2 group is dedicated to the development and application of machine learning (ML), deep learning (DL), and artificial intelligence (AI) techniques for the analysis and interpretation of astrophysical data and beyond. Our research covers a broad range of topics, from solar physics to galaxy evolution and cosmology expanding to bio-medicine projects.
Our group is engaged both in national and international level projects and collaboration. We have access to state-of-the-art computational facilities in Spain and internationally, enabling us to tackle complex astrophysical problems with cutting-edge machine learning techniques. Our team includes key members and leading contributors in major astronomical collaborations such as Euclid, DESI, and JWST, where we play an active role in data analysis and scientific exploration.
By integrating advanced computational techniques with observational and theoretical astrophysics, we aim to optimize data processing, refine predictive models, and uncover new insights from large astronomical datasets and simulations, pushing the frontiers of modern astrophysics.
Team Members
Carlos Westendorp
Faculty
Íñigo Arregui
Faculty
Gosia Siudek
Postdoc
Carlos Díaz Baso
Postdoc (RyC)
Eduardo Hartmann
Grad Student
Valentina Fontirroig Rojas
Grad Student
IA2 · RESEARCH
Featured Research
AI and advanced inference across astrophysics. Papers from 2024 onward, including preprints, with an IA2 member among the first three listed authors.
66 papers · Checked 2026-09-24 · Updated every two weeks
Semiresolved Stellar Populations as Distance Indicators
Neural posterior estimation turns partially resolved stellar populations into distance measurements.
Beyond traditional emission-line diagnostics: using autoencoders to uncover active galactic nuclei in DESI spectra
An autoencoder searches DESI spectra for active galactic nuclei beyond conventional emission-line diagnostics.
First detection of ultra-fast outflows in a quiescent galaxy
Bayesian spectral modelling with neural-assisted nested sampling tests evidence for an ultra-fast outflow in a quiescent galaxy.
A Pixel-by-Pixel Path to Population III Discovery with JWST
Pixel-level inference searches JWST images for signatures of Population III stars.
3DSTokesFlow: simulation-based inference for 3D Stokes profiles using flow matching
Flow matching estimates atmospheric parameters from three-dimensional Stokes profiles.
Marginal multi-object multi-frame blind deconvolution
Marginalizing over nuisance parameters improves multi-object, multi-frame restoration of astronomical images.
IA2 · GROUP MEETINGS
Meetings
17 September 2026
Kick-off meeting
12:00 pm WESTGTC room
1 October 2026
An overview of AI for solar physics at the IAC
Andrés Asensio Ramos
12:00 pm WESTGTC room
More meetings will be added throughout the academic year.
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