IAA-CSIC Severo Ochoa School on Artificial Intelligence and Machine Learning in Astronomy
Granada (Spain). : September 28 – October 2, 2026
Image Credits: AI Gemini
THE SCHOOL
Overview & Scientific Rationale
Modern astronomy is entering a data-intensive era in which Artificial Intelligence and Machine Learning are becoming essential scientific tools. From interferometric image reconstruction to source classification and cosmological inference, AI methods are transforming how astronomical discoveries are made.
The Instituto de Astrofísica de Andalucía - Severo Ochoa (IAA-SO) School on Artificial Intelligence and Machine Learning in Astronomy 2026 will provide graduate students, postdoctoral researchers, and early-career scientists with practical training in state-of-the-art AI techniques applied to real astronomical datasets from world-leading facilities.
Training Modules
The school is organized around five major technical pillars, each led by an expert in the field:
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Image Reconstruction: Optical/infrared interferometry deconvolution utilizing Deep Image Priors Neural Networks (DIP-NN).
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Radio Surveys: Data augmentation and automated morphological classification of radio sources using CNNs and Vision Transformers (ViT).
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Large-Scale Structure: Graph Neural Networks (GNNs) for classification and regression tasks on dark matter halo simulations.
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Gamma-Ray Astronomy: Deep learning-based image and waveform reconstruction for Imaging Atmospheric Cherenkov Telescopes.
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Unsupervised Learning: High-dimensional embeddings (t-SNE, UMAP, EVoC) and clustering algorithms applied to chemical tagging of star clusters.
Who should attend?
The school is designed for:
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MSc and PhD students in astronomy, physics, data science, or related disciplines
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Postdoctoral researchers
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Early-career scientists interested in AI applications in astronomy
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Researchers seeking practical experience with modern machine learning workflows
Prerequisites
Participants are expected to have:
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Basic Python programming experience.
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Familiarity with scientific computing tools (NumPy, Jupyter notebooks).
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Basic astronomy knowledge
Computing Environment
Tutorials will be delivered through Python notebooks. Software installation instructions and datasets will be distributed before the school. Participants should bring a laptop capable of running Python scientific workflows.
Learning outcomes
Participants will:
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Build and train modern neural network architectures
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Work directly with astronomical FITS datasets and simulations
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Develop practical experience with CNNs, Vision Transformers, Graph Neural Networks and unsupervised learning methods
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Understand strengths and limitations of AI approaches in astronomy
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Gain reproducible workflows applicable to their own research
Speakers & Lecturers
We are pleased to host an international team of lecturers specializing in different subsets of astronomical machine learning:
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Dr. Joel Sánchez Bermúdez Instituto de Astronomía (IA-UNAM), Mexico
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Dr. Andrea DeMarco Institute of Space Sciences and Astronomy (ISSA), University of Malta, Malta
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Dr. Farida Farsian Italian National Institute for Astrophysics (INAF), Osservatorio Astrofisico di Catania (OACT), Italy
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Dr. Tjark Miener University of Geneva, Switzerland / IAA Granada, Spain
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Dr. Rafael Garcia-Dias, King’s College London, United Kingdom
SCIENTIFIC ORGANIZING COMMITTEE
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Dr. Joel Sánchez Bermúdez (IA-UNAM, Mexico) — Chair
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Dr. Javier Moldón (IAA-CSIC, Spain) — Co-chair
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Dr. Cristóbal Bordiú (IAA-CSIC, Spain)
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Dr. Laura Darriba (IAA-CSIC, Spain)
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Dr. Rubén López-Coto (IAA-CSIC, Spain)
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Dr. Ginés Martínez Solaeche (IAA-CSIC, Spain)
LOCAL ORGANIZING COMMITTEE
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Dr. Laura Darriba (IAA-CSIC)
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Dr. Javier Moldón (IAA-CSIC)
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Dr. Cristóbal Bordiú (IAA-CSIC)
SCIENTIFIC PROGRAM & DAILY SCHEDULE
Sessions
Data Augmentation & Radio Classification
Hands on: Radio Survey Pipelines. Augment FITS cutout datasets of multi-class morphologies. Build and train a neural network classifier utilizing pretrained Convolutional Neural Network (CNN) or Vision Transformer (ViT) architectures.
Tutor: Andrea DeMarco
Graph Neural Networks in Cosmology
Hands on: Large Scale Structure Modeling. Convert Dark Matter halo simulations into graph structures. Deploy GNNs to classify halos (cluster vs. void areas) and run regressions to predict cosmological parameters (Omega_m parameter for a box of universe).
Tutor: Farida Farsian
DL Reconstruction in Gamma-Ray Astronomy
Hands on: CTAO Simulation & Analysis. Work with simulated data from the Cherenkov Telescope Array Observatory. Apply CNN-based methods to raw image and waveform data for particle classification, energy reconstruction, and arrival direction estimation.
Tutor: Tjark Miener
Unsupervised & Semi-Supervised Learning
Hands on: Chemical Tagging in Star Clusters. Benchmark dimensionality reduction methods (t-SNE vs. UMAP and the novel high-dimensional embedding algorithm EVoC) to identify star cluster members in the Pleiades using Gaia and chemical abundance datasets.
Tutor: Rafael Garcia-Dias
DIP-NN for Interferometry
Hands on: Interferometric Image Reconstruction. Deconvolve Sparse Aperture Masking data from JWST and reconstruct images from Event Horizon Telescope (EHT) data of M87* using Deep Image Priors Neural Networks.
Tutor: Joel Sánchez Bermúdez
Networking Activities
The school will include networking opportunities designed to facilitate interactions between participants and lecturers, promoting future collaborations across astronomy and machine learning communities.
REGISTRATION
How to register?
This School will be an in-person School. To formalize the participation you must fill in the mandatory fields in the registration form. Payment can be made by bank transfer or credit card.
Registration fee
The School fee will be 300 € for registrations completed before July 15. From July 15, a 50 € surcharge will apply. The registration fee includes participation in all lectures and tutorials, course materials, a daily coffee breaks, four lunches, welcome cocktail and School dinner.
Attendance limited to 40 participants to maximize interaction during hands-on sessions. Registration will be processed on a first-come, first-served basis.
Important dates
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First Announcement & Registration Opens: 12 June 2026
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Early bird Registration Deadline (Payment due): 15 July 2026
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Registration Deadline with surcharge (Final Payment due): 01 September 2026
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School dates: September 28 – October 2, 2026
Cancellation and modification policy
In case of cancellations or changes in the name of the attendees the following deadlines are applicable:
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90% of the fee will be returned, if participation is cancelled up to one month before the event
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50% of the fee will be returned, if participation is cancelled up to 15 days before the event
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0% otherwise
Code of conduct
The IAA-CSIC has a code of conduct that all registered participants should read and need to abide by
REGISTRATION FORM
VENUE
The School will take place at the Instituto de Astrofísica de Andalucía headquarters (IAA-CSIC), Glorieta de la Astronomía s/n, 18008 Granada, Spain. The IAA-CSIC is located 15 minutes walk from the city centre, and can be reached by bus lines S2, S0, 11 and 9.
Why Granada?
Granada combines world-class astronomy research with a historic city environment at the foothills of Sierra Nevada. Participants will attend the school at IAA-CSIC while experiencing one of southern Europe's major cultural destinations.
How to get to Granada?
Airports
Federico García Lorca Airport (GRANADA)
Federico García Lorca Airport is currently connected by six daily flights to Madrid and three daily flights to Barcelona. It is located 15km from the city centre, with buses to and from each flight. The cost of a taxi to or from the airport is ~30€.
Check here all airlines connections with Granada.
Pablo Picasso Airport (MALAGA)
The Pablo Picasso International Airport is located approximately 130km from Granada, connected to every European city with regular daily flights and, thanks to the motorway which links both cities, can be reached in just over one hour by car or bus.
Flights information and routes.
See the AENA website – Telephone: 958 245 200
Train
Modern trains connect Granada to all of Andalusia and to the main Spanish cities. The High Speed rail network has been operational since 2015, thus significantly lowering travel times.
Avenida de Andaluces, s/n 18014 Granada – Telephone: 902 320 320
Information, timetables and destinations on their website: www.renfe.es
Bus
Granada is very well connected thanks to its network of motorways and daily bus services to destinations all over the country.
Bus station
Address: Carretera de Jaén, s/n. 18014. Granada.
Telephone numbers: 958 18 54 80 / 958 25 13 58
ORGANIZATION
The organisers acknowledge financial support from the State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa" award for the Instituto de Astrofísica de Andalucía (grant CEX2021-001131-S 10.13039/501100011033)
Technical Secretariat · Baobab Eventos ai-ml@granadacongresos.com