Top selections for immediate go-ahead: • Joris De Ridder: Deep learning for Gaia variable sources. • Carlos Allende Prieto: Accelerating Gaia analysis via cloud tech We’re moving the "code to the data" to boost the exploitation of massive #ESA datasets from #Gaia and #Euclid

Exciting news for #SPACIOUS: Our Resource Allocation Committee has selected the first community-led challenges to launch on our #BigData platform. Congrats to the selected teams! Check our website for the full breakdown.

GAVS+ builds on the Gaia Archive Visualisation Service to deliver a cloud-ready, high-performance environment for interactive exploration of multibillion-row tables. New features include full Jupyter NB integration, enabling flexible visual analytics https://t.co/GpgNoPhuId

GUASOM provides an intuitive interface for training and visualising SOMs on massive spectroscopic or spectrophotometric datasets. An effective way to explore structure, identify patterns, and detect anomalies across high-dimensional data collections. https://t.co/PA5JyF2dnK

GANDALF is an open, python framework built on an adversarially trained autoencoder that disentangles key physical parameters in stellar spectra. Tests on synthetic and Gaia data show accurate parameter recovery and robust reconstruction performance. https://t.co/S1XrgFMHmw

SPACIOUS is expanding its toolbox with three new services GANDALF, GUASOM, and GAVS+, designed to support state-of-the-art machine learning, spectral analysis, and large-scale data exploration and strengthening SPACIOUS versatile environment for working with complex datasets.

The SPACIOUS Official Call for Users remains open. If your work involves large or complex datasets and would benefit from flexible, scalable computing, we invite you to submit applications before the closing date. Apply until November 16th, 2025: https://t.co/j47GtytBnO

SPACIOUS is present at the 2025 edition of the European Researchers' Night, a public event dedicated to science outreach, aimed at bringing research, innovation, and their protagonists closer to people of all ages in a fun and accessible way. https://t.co/dultlOfWV0

Initial Call for Early Test Users of SPACIOUS, a new cloud-native platform for data-intensive astrophysical research. If your work involves large or complex datasets and would benefit from flexible, scalable computing, apply/learn more:  https://t.co/DY5cDkSd7g @ESAGaia @ICC_UB

Disentangling Stellar Properties with GANs: New Method Published by R. Santoveña, C. Dafonte, and M. Manteiga presents an innovative deep learning approach for analysing stellar spectra, in Applied Soft Computing (Vol. 174, 2025). https://t.co/Jg2KkiVysI #ESAGaia #APOGEE

SPACIOUS Team Publishes GAN-Based Method for Gaia/RVS Spectra in Astronomy & Astrophysics (Vol. 694, A326, 2025) for disentangling stellar atmospheric parameters in Gaia DR3 RVS data using Generative Adversarial Networks (GANs). https://t.co/mrtV4lx46j #ESAGaia

First SPACIOUS Scientific Results Presented at the #EAS2025, Alfred Castro Ginard presented the talk “Statistical modelling the #ESAGaia DR3 selection function” - marking the first scientific results delivered using the SPACIOUS platform.

SPACIOUS@home: Help Explore the Universe from Home. We’re thrilled to announce SPACIOUS@home, an exciting citizen science initiative that invites you to contribute to cutting-edge astronomical research without ever leaving your home: https://t.co/HavAK6f8Ke.

Job offer at the University of Lisbon for a Research support technician. Research Field: Computer science Details at https://t.co/e3G7JbUrRr Application Deadline 26 Jul 2024 – 23:59 (Europe/Lisbon)