V. Ashley Villar, Anomaly Detection for Cosmic Explosion
Автор: Anomaly Detection for Scientific Discovery
Загружено: 2022-03-17
Просмотров: 196
Описание:
Speaker: V. Ashley Villar (Pennsylvania State University)
Abstract: The eruptions, collisions and explosions of stars drive the universe’s chemical and dynamical evolution. The upcoming Large Synoptic Survey Telescope 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 question: how do we classify transient events and separate the interesting “needles” from the “haystack” of objects? In this talk, I will discuss efforts to discover and classify unexpected phenomena using semi-supervised machine learning techniques. I will highlight the interplay between data-informed physics and physics-informed machine learning required to best understand the future LSST dataset of extragalactic transients.
Speaker's Bio:
V. Ashley Villar is an assistant professor of Astronomy and Astrophysics and Institute for Computational and Data Science co-hire at Penn State. She received her BS in Physics from MIT and her PhD in Astronomy and Astrophysics from Harvard. She then completed a Simons Foundation postdoctoral fellowship at Columbia University. Her research uses observations of cosmic, transient phenomena to study the death of stars.
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