Astro-AI Analytics is a topic/research group led by Professor Yvonne Becherini (YB) at the Astroparticule et Cosmologie Laboratory (APC) within the Department of Physics at Université Paris Cité.
It focuses on the development and application of Artificial Intelligence (AI), Machine Learning (ML), and Data Science methods for astrophysics, with a particular interest in multi-messenger astronomy.
The work carried out in this area combines advanced computational approaches with astrophysical research to optimize data-analysis pipelines, extract information from large and complex datasets, and improve observational strategies in high-energy astrophysics.
Alongside these research activities, YB teaches PhD-level courses in Applied Data Analytics, in addition to regular teaching in the Physics programme, and serves as the Director of the Graduate School Earth-Planet-Universe at Université Paris Cité.
AI and machine learning for astrophysics and astroparticle physics
Multi-messenger astronomy and neutrino-source studies
Time-series analysis, variability, and representation learning
Event classification, calibration, and scientific inference
Data-driven methods for large and complex observational datasets
The HESS (High Energy Stereoscopic System) gamma-ray observatory is a leading ground-based telescope array designed to detect very-high-energy (VHE) gamma rays from astrophysical sources. Located in Namibia, HESS consists of multiple Cherenkov telescopes that capture the brief flashes of Cherenkov light produced when gamma rays interact with Earth's atmosphere. The observatory has made significant contributions to the study of active galactic nuclei (AGN), supernova remnants, pulsar wind nebulae, and the Galactic Centre, helping to map the most energetic processes in the universe. HESS plays a crucial role in multi-messenger astrophysics, complementing observations from space-based telescopes and other cosmic messenger experiments.
KM3NeT (Cubic Kilometre Neutrino Telescope) is an underwater neutrino observatory designed to detect high-energy cosmic neutrinos. Deployed in the deep Mediterranean Sea, KM3NeT consists of vast arrays of optical modules that capture the faint flashes of Cherenkov light produced when neutrinos interact with water. The observatory is structured into two main detectors: ORCA, optimized for studying atmospheric neutrinos and neutrino oscillations, and ARCA, dedicated to identifying astrophysical neutrino sources such as active galactic nuclei (AGN), gamma-ray bursts, and supernovae.
The ALTO CoMET project was a completed research initiative focused on developing a wide-field gamma-ray and cosmic-ray detection array using Cherenkov light detectors. The project, funded at a level of 600k€ by several public and private institutions, including the Crafoord Foundation, included a prototype phase at Linnaeus University in Växjö, Sweden, where detector designs were tested and optimized for sensitivity to very-high-energy gamma rays. ALTO explored innovative methodologies for event reconstruction and background rejection, contributing to advancements in gamma-ray astronomy. The project resulted in two peer-reviewed publications, providing valuable insights that can inform the development of future Cherenkov detector arrays.