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About

M. J. Graham is a prominent astronomer and data scientist whose work sits at the intersection of time-domain astronomy, automated survey infrastructure, and machine learning-driven classification. Graham has made foundational contributions to the Zwicky Transient Facility (ZTF), a state-of-the-art robotic sky survey at Palomar Observatory capable of scanning the entire northern sky at unprecedented speed and depth. His involvement in ZTF's data processing pipeline, products, and archive — the cornerstone paper of which has accumulated over 1,170 citations — has helped establish ZTF as one of the most productive transient-detection facilities in modern astronomy. Graham also pioneered braai, a deep-learning convolutional neural network for real/bogus classification that distinguishes genuine astrophysical events from imaging artifacts, earning over 155 citations and becoming an essential tool for large-scale survey automation. His earlier work on astronomical network event and observation notification protocols reflects a long-standing commitment to interoperable observatory systems. More recently, Graham has extended machine learning applications to supernova spectral classification through the CCSNscore framework. Across his career, Graham's technical innovations have directly enabled the discovery and characterization of transient phenomena at scales previously unattainable.