GWFREERIDE: Carving the AI Gradient in Gravitational-Wave Astronomy
Sexten (Italy) - Jan 26-30, 2026

Gravitational-wave astronomy is rapidly advancing, driven by expanding observational datasets from LIGO-Virgo-KAGRA and pulsar timing arrays. Harnessing these increasingly complex data for astrophysical discovery requires accurate modeling of signals and noise, efficient detection methods, and scalable Bayesian inference techniques.

Artificial intelligence (AI)—including simulation-based inference and advanced architectures like transformers and diffusion models—is reshaping data analysis across science, including gravitational waves. AI-driven techniques  already enhance detection sensitivity, accelerate parameter estimation, and mitigate non-Gaussian detector noise. Yet next-generation observatories such as LISA, the Einstein Telescope, and Cosmic Explorer, will present unprecedented challenges: millions of detectable sources, overlapping signals, and more complex astrophysical signals. Fast, reliable inference will be crucial for timely multi-messenger follow-up and continued scientific breakthroughs.

This workshop brings together experts from gravitational-wave astronomy, artificial intelligence, and astrophysical modeling to define key challenges and opportunities for AI in the coming decade. Through interdisciplinary discussions, participants will define pathways to enhance detection and parameter estimation, waveform modeling, and population analysis. The goal is to develop a strategic roadmap for integrating AI methods into gravitational-wave science and maximize the return from future observational campaigns.