11-07, 11:15–11:30 (US/Arizona), Talks
New software developments in data post-processing are being made within the SKA precursor communities to enable extraction of science information from radio images in a mostly automated way. Many of them exploit HPC processing paradigms and machine learning (ML) methodologies for various tasks, such as source detection, object or morphology classification, or anomaly detection.
In this context, we are developing several ML-based tools to support the scientific analysis conducted within the ASKAP EMU and MeerKAT surveys. One tool employs deep neural networks to detect compact and extended radio sources and imaging artifacts from radio continuum images. Another tool uses different ML techniques to classify compact sources into different classes (galaxy, QSO, star, pulsar, HII, PN, YSO) using radio and infrared multi-band images. Furthermore, we have developed self-supervised models for radio data representation learning, and generative models to produce synthetic radio image data for data challenges or model performance boosting.
These tools have been trained and tested on different radio survey data including the ASKAP EMU survey. An overview of the results achieved will be presented at the workshop, along with details on the ongoing activities and future prospects.
Simone Riggi received the Ph.D. in Physics from the University of Catania (Italy) in 2010. He currently holds a permanent position as Research Technologist in the IT and Radioastronomy group of the INAF-Osservatorio Astrofisico Catania (Italy). Previously, he was a post-doctoral fellow at the Universidad de
Santiago de Compostela (Spain), Centro Siciliano di Fisica Nucleare e Struttura della Materia (Italy) and visiting student at the Forschungszentrum Karlsruhe (Germany).
His research activity mainly focuses on Radioastronomy, High-Energy Cosmic Rays, Muon Tomography, Computer Science. He was involved and contributed to several research and technological projects, among them the Square Kilometer Array (SKA) as member
of the Dish and Telescope Manager consortia, the Australian Square Kilometre
Array Pathfinder (ASKAP) as member of the EMU survey, the H2020 AENEAS
project for the design of SKA Regional Data Centers, the Pierre Auger Observatory and the Muon Portal project. Present technological activities include the development of monitoring and control systems for medium/large scientific facilities, simulation and modelling, design and development of data analysis software for astronomy and astroparticle physics, distributed computing and
scientific visualization. He is author/co-author of more than 100 scientific publications and conference communications in these research and technological fields.