Hello! I’m Gregory Paek, an astronomer captivated by the transient universe and its fleeting phenomena. My work bridges advanced observational techniques and computational innovation to uncover the secrets of transient, with a special focus on kilonovae, their diversity, and their roles as optical counterparts of gravitational waves and gamma-ray bursts.

I have extensive experience with imaging observations and data analysis, particularly in optical and near-infrared astronomy, and have developed robust pipelines to process and analyze large datasets. Over the years, I’ve actively contributed as part of various survey teams, collaborating on studies of supernovae, gamma-ray bursts, and other transient phenomena. These collaborations have deepened my understanding of the transient sky and enriched my approach to multi-wavelength follow-ups.

Whether you have questions, collaboration ideas, or just want to share a thought, I always welcome engaging discussions, teamwork, and even casual small talk.

My scientific interests lie at the intersection of transient astrophysics and data-driven analysis. I specialize in:

Gravitational-wave multi-messenger astronomy
(e.g., kilonovae, short GRBs, optical counterparts to GW sources)

Photometric classification of transients using Machine learning and anomaly detection

Large-scale survey analysis (e.g. developement of data reduction pipeline and photometric calibration of medium-band filters) and observational follow-up optimization

As part of my doctoral research, I developed a photometric SED classifier using 7DT medium-band filters to efficiently distinguish kilonovae and other rare transients from common supernovae. My work explores ways to maximize scientific return during the early phases of transient detection, especially when light curves are not yet available.

Publications

Honors

• GWPAW2022 Poster Award (1000AUD)