# The Present and the Future of Machine Learning for Multi-Messenger Astrophysics

- Institution: CERN
- Speaker: Michael Coughlin
- Year: 2026
- Language: English
- Subjects: Computer science, Astronomy and space
- Source: [CERN](https://videos.cern.ch/record/3025639)
- Licence: [CERN](https://copyright.web.cern)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

With the detection of compact binary coalescences and their electromagnetic counterparts by gravitational-wave detectors, a new era of multi-messenger astronomy has begun. In this talk, I will describe how machine learning is enabling the gravitational-wave community to make very low-latency detection and parameter estimation possible within the alert system. I will then discuss how current ground based optical surveys and dedicated follow-up systems are integrating machine learning into their standard work flows, with examples from both current and near future surveys. We will close with near-term prospects for the field.

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## Lectures

1. [The Present and the Future of Machine Learning for Multi-Messenger Astrophysics](https://invisiblenetwork.ai/learn/cern/3025639/e578a8f2b88c), 18 min (CERN's player)