I am a research fellow at the Gravity Exploration Institute. I use gravitational-wave observations as probes to study the Universe.
In 2015 the LIGO observatories detected the first gravitational-wave signal. The signal, known as GW150914 (meaning it was detected on 14th September 2015) is the consistent with what General Relativity predicts for the gravitational-wave signal that would be emitted by a pair of merging black holes. This observation has ushered in the era of gravitational-wave astronomy!
Since then, the wolrd wide network of gravitational wave detectors have observed 50 gravitational-wave events from merging black holes and neutron stars!
My research focus is to use gravitational-wave observations to understand the Universe.
To achieve this goal I emply a variety of methods, the most important methods being physical modelling, machine learning and Bayesian inference.
I have developed models for binary black holes, binary neutron stars and mixed neutron star-black hole binaries as well as developed computationally efficient surrogate waveform models using artificial neural networks.
Currently I am developing tools and methods designed to efficiently consume the big data products that gravitational-wave astronomy is providing. The main areas I am investigating are Hamiltonian monte carlo Bayesian samplers and neural network-based waveform models that can be parallelised on GPUs.