Research

develop methods and conduct large simulations to understand what gravitationalSummary:
waves emitted by compact object (black hole and neutron star) mergers can

My research focuses on Gravitational Wave Paleontology: studying massive stars from their ‘remnants’ as compact object coalescences, with the goal to answer some of the key questions in gravitational-wave astronomy today: How do these gravitational-wave sources form? What can we learn from them about the formation, lives, and explosive deaths of massive stars across cosmic time? How do these sources help to enrich the universe with heavy metals over cosmic time?

 
When pairs of stellar-mass black holes and neutron stars across our vast universe collide, they unleash bursts of gravitational waves that can now be detected on Earth since the first observation of a binary black hole merger in 2015. The detectable properties of these double compact object mergers, like their masses, carry valuable information about the physics of black holes and neutron stars and probe the massive stars that once formed them. These detections open this new frontier of gravitational-wave paleontology. Making the most of these gravitational-wave observations requires comparing the observed properties of the black hole and neutron star mergers, such as their rates, masses, and spins, to theoretical models of their formation pathways. In my work I  address the key bottleneck in this endeavor: the so-called progenitor Uncertainty Challenge: uncertainties within the theoretical models are so large, and the models so computationally expensive, that learning about the underlying fundamental physical processes in massive star evolution from gravitational-wave observations is challenging. 

Together with my international team of collaborators and students, I am developing new tools, methods, and simulations to improve on this and open the field of gravitational-wave paleontology and learn about the lives of massive stars across cosmic time. My research focuses on building and understanding stellar evolution models, developing new machine learning and AI techniques to improve computational costs, understanding the formation of gravitational-wave sources across cosmic time, and understanding the star formation and enrichment histories of our Universe. My research spans topics including massive stars, gravitational waves, binaries, black holes and neutron stars, stellar evolution, pulsars, astro-statistics, AI, Machine Learning, double compact object merger rates and properties, and population synthesis models — I also have a passion for projects that try to strengthen support resources for software, open data, and early-career astronomers and physicists [e.g., this and this]. 


tional simulations, and tackles the key bottleneck in gravitational-wave astrophysics:
the “Uncertainty Challenge” with the ultimate goal to learn about fundamental
physical processes in our Universe in the new Big Data gravitational wave era.

Simulating billions of stars and the black holes & neutron stars they form 

Investigating the cosmic star formation history using Gravitational Waves 

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Future Gravitational Wave Detectors

Figure showing the increase in detections expected in the coming years with gravitational waves

Investigating the lives of binary stars 

Developing Statistical, AI, and ML techniques for stellar populations & GWs

Supporting Software,  Big and Open Data, and Reproducibility/Transparency in Science 

Resources for Early Career Astronomers & Their Supporters

Banner with the CfA logo saying "Early career astronomers & their supporters workshop series". On the right a cartoon of a PhD student balancing PhD topics such as imposter syndrome, jobs, writing etc. is shown