My research focuses on the physics of the earliest stages of the evolution of the universe and of the correspondingly high energies that cannot be reproduced in laboratories. I work on experiments that probe the content and properties of the Universe today: LIGO, which aims to measure gravitational waves generated by various events and processes in the universe; and SuperCDMS, which aims to detect dark matter in the form of new weakly interactive massive particles.
My group uses Bayesian inference to extract information about the gravitational wave sky from data acquired by LIGO detectors. This includes imaging the gravitational wave sky and estimating the frequency, directionality, and polarization properties of the gravitational wave background on the sky. We use similar techniques to study implications of dark matter searches for many-dimensional parameter space of fundamental particle models. We also use machine learning techniques for removing environmental contamination from gravitational-wave data and to optimally extract information from dark matter cryogenic semiconductor detectors.