Gayathri V, Ph.D.

Postdoctoral Associate, University of Wisconsin Milwaukee

I am a Postdoctoral Associate at the University of Wisconsin Milwaukee, working with Prof. Jolien Creighton and Prof. Patrick Brady (LIGO Spokesperson). My research centers on Gravitational Wave Astrophysics, with a focus on the detection, interpretation, and computational analysis of gravitational wave events. I have been actively involved in developing machine learning-enhanced algorithms for gravitational wave observatories.

I earned my PhD from the Indian Institute of Technology Bombay under the supervision of Prof. Archana Pai and previously held a postdoctoral position at the University of Florida, collaborating with Prof. Imre Bartos. My work explores key challenges in the search for gravitational wave transients, contributing to the LIGO-Virgo Collaboration and advancing our understanding of binary black hole mergers.

Research Interests:

1. Gravitational Wave Detection Algorithms:

Developing algorithms for detecting gravitational wave transients using interferometric detectors like LIGO and Virgo.

2. Intermediate-Mass Black Hole Binaries and Eccentric Binary Searches:

Investigating gravitational wave signals from these exotic systems in Advanced LIGO and Virgo data.

3. Machine Learning for Gravitational Wave Science:

Applying machine learning to enhance detection algorithms and improve the interpretation of gravitational wave events.

4. Noise Veto Techniques:

Crafting strategies to differentiate genuine gravitational wave signals from noise, improving detection reliability.

Recent Research Highlights:

Binary Black Hole Mergers in Active Galactic Nuclei:

Collaborating with researchers from the University of Florida and Columbia University to understand the role of accretion discs in black hole mergers and estimate gravitational wave rate densities from this formation channel.

GW190521 Event Analysis:

Investigating the massive binary merger GW190521 using eccentric numerical relativity waveforms, in collaboration with experts from Rochester Institute of Technology and others, offering insights into the event’s origins in dense environments.

Coherent WaveBurst Search Algorithm Enhancement:

Leading efforts to improve the coherent WaveBurst algorithm with machine learning to detect rare binary mergers across a global network of gravitational wave observatories.