The eruptions, collisions and explosions of stars drive the universe’s chemical and dynamical evolution. The upcoming Legacy Survey of Space and Time will drastically increase the discovery rate of these transient phenomena, bringing time-domain astrophysics into the realm of “big data.” With this transition comes the important questions: how do we classify transient events and separate the interesting “needles” from the “haystack” of objects? In this talk, I will highlight exciting prospects for LSST and describe ongoing efforts to prepare for this data influx, including new approaches to manage the vast “haystack” of routine transients. I will then focus on how anomaly-driven discovery methods have already proven successful at uncovering rare and unexpected phenomena, including the recent identification of a merger-driven supernova, and discuss what discoveries may await us in the Rubin era.
