Research

My research falls into an emerging and growing cross-disciplinary field called astrostatistics. Astrostatistics is at the interface of astronomy and statistics; it includes the application of modern statistical tools to astronomy research, and also involves developing new statistical tools for astronomy which may be useful to other disciplines too. You can see a list of publications at the bottom of this page.

On the statistics side, I am interested in Bayesian inference, adaptive and novel MCMC methods, and probability distributions. Recently, I have also been learning about spectral analysis — the area of statistics that studies time series data in the frequency domain. My motivation to learn about these topics is fueled by my research interests in astronomy and astrophysics. I am an astrophysicist first and foremost, afterall!

My main research interests in astronomy are related to the Milky Way Galaxy. I have developed a method to estimate the total mass of the Milky Way and its dark matter halo by using the positions and velocities of "tracer" objects such as globular clusters and dwarf galaxies. Many studies have tried to estimate the mass of the Milky Way, but the estimates span a large range of masses and many are in stark disagreement with one another. To obtain a better estimate, I adopted a hierarchical Bayesian approach which allows for the inclusion of measurement uncertainties and incomplete data. With this new method, I estimated a cumulative mass profile — as opposed to point estimates — for the Galaxy (see publication list below).

I have also become interested in asteroseismology and, more generally, the analysis of time series data in astronomy. I am researching new methods from the statistics literature that estimate periodicities in time series data which are unevenly sampled in time. Reliable methods for analyzing such time series will be needed with the upcoming data form the Zwicky Transient Facility and the Large Synoptic Survey Telescope.