Andrew Kaiser

Andrew has spent the majority of his research experience exploring and characterizing sources of noise and signals in current and future gravitational wave (GW) detectors using frequentist and Bayesian methods. His work revolves specifically around three projects: 
• Estimating the response strength in current and future gravitational wave detectors under a variety of designs to coalescing black hole binaries using frequentist methods nicely packaged in the Python package gwent. 
• Assessing the potential of pulsar timing arrays (PTAs) to detect multiple GW backgrounds through simulation and recovery work. 
• Holistically examine pulsar timing parameters inside PTAs’ current GW detection pipeline using non-linear parameterization of pulsar timing models in tandem with noise and dispersion measure modeling. 
For all of these projects he worked alongside his colleagues as a full member of NANOGrav. In addition to these main projects, he has broader interests searching for individual GW sources, data analysis, pulsar noise characterization, and data visualization.