AI for Gravitational Waves Workshop
This workshop is on how AI and machine learning are reshaping gravitational wave science across four themes: Data Analysis (low-latency detection, parameter inference, transient searches, interpretability), GW Simulation (fast waveforms, surrogate modeling, differentiable simulation, uncertainty quantification), Real-Time Data Processing (streaming ML, scalable inference, GPU/FPGA acceleration, model compression), and Detector Operations (monitoring, noise hunting, data quality, predictive maintenance).
The programme features keynote talks from the LVK, ET, LISA, MMA, and PTA, bringing together ML researchers, GW astronomers, instrumentalists, and computing experts to surface shared challenges and collaboration opportunities ahead of the next observing runs and future missions.
Invited speakers
- Viola Sordini (IPN, Lyon)
- Michele Valisneri (ETH, Zurich)
- Paolo Pani (Sapienza University of Rome)
- Stas Babak (CNRS, Paris)
- Daniel Muthukrishna (MIT, US)
- Max Dax (ELLIS Institute and MPI, Tübingen)
- Deep Chatterjee (MIT)
- Michael Coughlin (University of Minnesota)
- Huw Haigh (Austrian Academy of Sciences)
- James Alvey (University of Cambridge)
- Melissa Lopez (Nikhef and Utrecht University)
- Uddipta Bhardwaj (ETH)
- Tomislav Andric (Gran Sasso Science Institute)
- Nikhil Mukund (MIT)
- Christina Reissel (MIT)
- Jonathan Klimesch (University of Tübingen)
- Siddharth Soni (University of California)
Scientific committee
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Elena Cuoco (University of Bologna)
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Valerie Domcke (CERN)
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Jan Harms (Gran Sasso Science Institute)
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Gianluca Inguglia (Austrian Academy of Sciences)
- Erik Katsavounidis (MIT)
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Samaya Nissanke (DESY, German Centre for Astrophysics DZA)
Organising committee
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Katya Govorkova (MIT)
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Eric Moreno (MIT)
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Maurizio Pierini (CERN)
