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About

B. Rusholme is a prominent astronomer and data scientist whose work sits at the intersection of large-scale sky surveys, astronomical data processing, and machine learning applications in astrophysics. Best known for contributions to the **Zwicky Transient Facility (ZTF)**, Rusholme has played a central role in developing the data processing pipelines, archival systems, and computational infrastructure that make this ambitious robotic time-domain survey possible. The flagship ZTF data systems paper alone has accumulated over 1,170 citations, reflecting the facility's foundational importance to modern transient astronomy. Rusholme's expertise extends into artificial intelligence-driven discovery, most notably through *braai*, a deep-learning convolutional neural network classifier designed to distinguish genuine astrophysical events from image artifacts — a critical challenge in high-volume surveys — earning over 155 citations since 2019. More recently, Rusholme has contributed to *CCSNscore*, a multi-input deep learning tool for classifying core-collapse supernovae from spectroscopic data, demonstrating a sustained commitment to automating the classification bottlenecks created by the sheer scale of modern sky surveys. Across this body of work, Rusholme has helped transform how the astronomical community detects, processes, and interprets transient phenomena at unprecedented speed and scale.