On Friday, the 10th of January, PhD students Ann Malz and Mattia Emma led the organisation of a Royal Astronomical Society (RAS) meeting on Gravitational Wave Analysis in the Era of Machine Learning.
The morning began with discussing searches and parameter estimation for ground-based detectors. This raised great discussions about whether ML can discover new signal classes, the need for shared infrastructure and tests, and the balance of speed improvements versus the capacity to discover new patterns. The afternoon then focused on next-generation detectors and future challenges, leading to more fascinating discussions about the need for ML when we have thousands of sources and how ML approaches can complement traditional methods.
The recording of the meeting and a summary will be posted on the RAS website in due course, but we thank all the organisers (Ann Malz, Mattia Emma, Greg Ashton, Vivien Raymond, and John Veitch), panellists, and the RAS for the support.
https://ras.ac.uk/events-and-meetings/ras-meetings/gravitational-wave-analysis-era-machine-learning