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Adam Miller is an optical survey astronomer working at the intersection of time-domain astronomy and data science, with the aim of improving the understanding of stellar evolution. His recent efforts have focused on developing machine learning methods to streamline the discovery and classification of electromagnetic transients. In 2023, Adam's research group produced the first-ever fully automated observation, identification, follow-up request, spectroscopic classification, and public announcement of a supernova to the astronomical community. His work emphasizes rapid, automated discoveries of supernovae, significantly fueling studies into the nature of stellar explosions. In particular, ongoing efforts are concentrated on understanding the progenitor systems of Type Ia supernovae (SNe Ia) and the low mass white dwarfs that produce a significant fraction of normal SNe Ia, which are observed through a double detonation mechanism. Adam serves as the Director of the La Silla Schmidt Southern Survey, where his group develops new artificial intelligence systems to identify double-detonation SNe. Additionally, he is the Director of the LSST-DA Data Science Fellowship Program, which trains graduate students in astronomy and related fields in cutting-edge data science methods necessary for analyzing data from the Vera C. Rubin Observatory’s Legacy Survey of Space and Time.
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