most citedBringing computation to the data: A MOEA-driven approach for optimising data processing in the context of the SKA and SRCNet

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

astro-ph.IM2026

Towards the exploration of astrophysical datacubes through volumetric rendering within CARTA

Ixaka Labadie-García, Adrianna Pińska, Angus Comrie +5

Data products from astrophysical observations may contain three or more dimensions: most commonly two spatial dimensions and a third spectral dimension, and possibly additional axe…

cs.DC2026

Bringing Computation to the data: Interoperable serverless function execution for astrophysical data analysis in the SRCNet

Manuel Parra-Royón, Julián Garrido-Sánchez, Susana Sánchez-Expósito +10

Serverless computing is a paradigm in which the underlying infrastructure is fully managed by the provider, enabling applications and services to be executed with elastic resource…

cs.DC20261 cited

Bringing computation to the data: A MOEA-driven approach for optimising data processing in the context of the SKA and SRCNet

Manuel Parra-Royón, Álvaro Rodríguez-Gallardo, Susana Sánchez-Expósito +6

The Square Kilometre Array (SKA) will generate unprecedented data volumes, making efficient data processing a critical challenge. Within this context, the SKA Regional Centres Netw…

astro-ph.GA2025

Classification of HI Galaxy Profiles Using Unsupervised Learning and Convolutional Neural Networks: A Comparative Analysis and Methodological Cases of Studies

Gabriel Jaimes-Illanes, Manuel Parra-Royon, Laura Darriba-Pol +5

Hydrogen, the most abundant element in the universe, is crucial for understanding galaxy formation and evolution. The 21 cm neutral atomic hydrogen - HI spectral line maps the gas…