My research seeks to connect experimental data with theory at the frontiers of new or unexpected phenomena. Its current focus is data analysis for gravitational wave (GW) signal detection, and use of such detections to investigate open problems in astrophysics and fundamental physics.
Having previously worked in particle theory and particle cosmology, I switched fields to GW astronomy in 2009: highlights since then have been analysis methods and results crucial to detection of the first GW signals; methods for inference on the astrophysical population of compact binary systems; and contributions to the science vision of the planned Einstein Telescope facility.
My main contributions to the ground-breaking LIGO-Virgo collaboration discovery of massive stellar black hole mergers in 2015 were methods for separating compact binary coalescence (CBC) signals from instrumental data artefacts, and for estimating statistical detection confidence; I also contributed to Bayesian methods for inferring merger rates in the local Universe. During subsequent observing runs I continued to optimise the PyCBC detection pipeline’s sensitivity, focusing increasingly on low latency detection and inference for rapid candidate followup. Recently I started a program to reconstruct the binary merger population without restrictive model assumptions. I am also interested in related problems of CBC detection and population inference for the future Einstein Telescope and LISA detectors.