Dr Metha Prathaban

PhD thesis title: Next-generation gravitational-wave inference: Bayesian methods for an AI era

The 2015 Nobel Prize-winning detection of gravitational waves heralded a new epoch in our study of the universe. For millennia we have observed the cosmos by seeing it; gravitational waves now allow us to 'hear' it, by listening to the vibrations of spacetime itself. These cosmic messengers are generated by astrophysical phenomena such as the collision of black holes, and are rapidly transforming how we probe black hole formation, cosmic expansion, and fundamental physics.

However, this scientific promise is predicated on solving a formidable data problem. Faint signals are buried in instrumental noise, and to extract source properties, we rely on certain analysis techniques. The rigour of these methods, however, comes at an immense computational cost. A single analysis can take days to complete, hindering the search for new physics. My doctoral research has confronted this by developing innovations at the intersection of algorithmic theory, machine learning, and high-performance computing.

After the PhD

I am taking up a Research Fellow position at the University of Southampton, in the Gravity group, to continue my research into novel methods for gravitational-wave data analysis using AI.