My current research interests include using machine-learning methods to do Bayesian parameter estimation on eccentric binary black holes. With the coming runs of LIGO where we can expect O(100) events. Therefore, rapid and reliable inference of gravitational wave events is necessary. With machine-learning we can achieve this. I am also interested in ringdown tests of general relativity and black hole quasi-normal modes. By doing parameter estimation on the final phase of a black hole merger, we can put constraints on other theories of gravity.
2017-2021 Bachelor of Science in Physics from University of Florida
under the direction of Prof. Imre Bartos where I worked on using genetic
algorithms to improve inference of electromagnetic follow up to
2017-2021 Bachelor of Science in Mathematics from University of Florida where I worked on using persistent homology (topological data analysis) to predict the redshift of clusters in the cosmic web.
Since 2021 Ph.D student at the University of Maryland
Starting from Jan. 2022 I am a Ph.D student at the Max Planck Institute for Gravitational Physics working under the direction of Alessandra Buonanno and Jonathan Gair.