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About

Umaa Rebbapragada is a researcher whose work sits at the dynamic intersection of astronomical data science, machine learning, and time-domain astrophysics. She has made significant contributions to the Zwicky Transient Facility (ZTF), a groundbreaking robotic sky survey that scans the entire northern sky using a 600-megapixel camera mounted on the Palomar 48-inch Schmidt Telescope. Her involvement in ZTF's data processing infrastructure and image pipeline development has helped underpin one of modern astronomy's most productive transient-detection systems, with her foundational ZTF data processing paper accumulating over 1,170 citations — a testament to the facility's far-reaching scientific impact across the community. Among her most notable individual contributions is the development of *braai*, a convolutional neural network classifier designed to distinguish genuine astrophysical transients from image artifacts — a critical challenge in large-scale automated surveys. This "real-bogus" classifier, cited over 150 times, exemplifies her expertise in applying deep learning to solve practical astronomical problems at scale. Through her sustained contributions to ZTF's data systems and AI-driven detection methods, Rebbapragada has helped shape how modern observatories handle the era of petabyte-scale sky surveys, making her work essential reading for researchers in both astrophysics and astronomical informatics.