03/18/26
Led by undergraduate researcher Adam Boesky, our new paper presents SPLASH, a machine-learning pipeline that classifies supernovae using only their host-galaxy photometry, published in The Astrophysical Journal Supplement Series. Read the paper here.03/03/26
Led by graduate student Karthik Yadavalli, our new paper presents a grid of 1800 radiative-transfer models for stripped-envelope (Type Ib/c) supernovae to enable improved ejecta parameter inference, published in The Astrophysical Journal. Read the paper here.08/14/25
Our new ApJ paper reports a merger-driven supernova flagged by an AI anomaly detection system. Read the paper. Press: Reuters · BBC World Service · Washington Post · Astronomy Magazine · USA Today.06/23/25
Our new paper on a large sample of Type IIn supernovae was published in The Astrophysical Journal. Read the paper here.02/19/25
Dr. Ashley Villar has been awarded a prestigious Cottrell Scholarship from the Research Corporation for Science Advancement. Read more here.12/30/24
Our new paper on understanding the rate of precursors for Type II (H-rich) supernovae in LSST was published in The Astrophysical Journal. Read the paper here.12/19/24
Our paper presenting the first multi-modal foundation model for supernovae was published in Machine Learning: Science and Technology. Read the paper here.12/11/24
Our new paper on utilizing host galaxies to better classify supernovae was published in The Astrophysical Journal Supplement Series. Read the paper here.10/21/24
Dr. Ashley Villar has been awarded a 2024 Packard Fellowship for Science and Engineering. Read more here.01/23/24
We have a new group website!