Research

The Gravitational-Wave Transient Catalogs (GWTC) are the LIGO–Virgo–KAGRA Collaboration's official record of every confident compact-binary merger. I help manage the catalogs for the fourth observing run (O4): I co-chair the GWTC working group in the collaboration and am the editorial chair of the GWTC-5.0 results paper, which reports the candidates up to the second part of O4 (O4b).

As the GW170817 discovery demonstrated, the primary route to multi-messenger observation is to issue a public alert and point electromagnetic telescopes at the inferred sky location. However, the inverse approach is equally possible: short gamma-ray bursts and other electromagnetic transients tell us where and when to look for preceding GW signals. I am developing a targeted mode of the GW search pipeline that folds the sky position and time of an external trigger into its likelihood-ratio ranking statistic. This recovers weaker GW signals that an all-sky search would miss, while keeping false alarms under control, and enables rapid follow-up of electromagnetic transients.

GstLAL is one of the LVK’s real-time matched-filtering pipelines that issue public alerts within seconds of a merger, and it made the first low-latency detection of GW170817. I worked on its readiness for O4, including the template bank used throughout the run, and on event follow-up during observing runs. I am now part of the team building its successor, SGNL, which reimplements GstLAL’s matched filtering in a lightweight Python streaming framework with GPU acceleration and cuts the median alert latency roughly in half.

I am one of the core developers of the GstLAL and SGNL pipelines, specializing in their statistical post-processing. Ahead of O4, I led upgrades to GstLAL’s ranking statistic: removing signal contamination from the background, adding the bank-ξ² statistic, upgrading the ρ–ξ² signal model and integrating KAGRA. Together these improved the pipeline’s sensitivity by roughly 15–20%.

The combined hum of countless unresolved sources forms a stochastic gravitational-wave background, whose brightness may vary across the sky and trace structures such as the Galactic plane. I developed a Bayesian framework that infers the physical parameters of a targeted anisotropic background and chooses the angular resolution from the data itself. I applied it to O3 data to search for millisecond pulsars and extended it to test non-tensorial polarizations beyond general relativity. I co-chair the LVK's anisotropic stochastic-background working group.

Ultralight bosons, dark-matter candidates beyond the Standard Model, can extract spin from black holes through superradiance. The resulting clouds emit nearly monochromatic gravitational waves, and the signals from the whole black-hole population adds up to a stochastic background. My Ph.D. work modeled this background for scalar and vector bosons and searched Advanced LIGO data for it. Under optimistic black-hole spin assumptions, vector bosons with masses of 0.8–6.0 × 10⁻¹³ eV are excluded.