# Nihar Gupte

Location Potsdam

### Main Focus

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.

__Publications__

Here are links to my publications: from INSPIRE, and from the ADS database.

### Curriculum Vitae

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
gravitational waves.

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.