Sara Frederick
Papers
1
Total Citations
158
H-Index
1
About
Sara Frederick is an astrophysicist whose work sits at the intersection of machine learning and time-domain astronomy. She is best known for developing *braai*, a convolutional neural network that serves as a real-bogus classifier for the Zwicky Transient Facility (ZTF). This deep-learning tool, detailed in her highly cited 2019 paper (158 citations), is critical for efficiently separating genuine astrophysical transients—like supernovae and variable stars—from spurious artifacts in the flood of ZTF survey data. By automating this classification, Frederick’s work has dramatically accelerated the discovery pipeline, enabling astronomers to focus on the most promising candidates for follow-up. Her contributions are foundational to modern transient science, helping to manage the data deluge from wide-field surveys. Frederick’s research exemplifies how cutting-edge computational methods are reshaping observational astronomy, and her *braai* classifier remains a key component of ZTF operations, directly impacting the detection of everything from kilonovae to active galactic nuclei.
Research Focus
Key Achievements
Top Papers
- 1Real-bogus classification for the Zwicky Transient Facility using deep learning158 citations · 2019