Ashley Villar

Ashley Villar is an Assistant Professor of Astronomy at the Center for Astrophysics at Harvard University. Her research focuses on the intersection of astrophysics and machine learning, particularly in the study of supernovae, transient phenomena, and circumstellar interactions. She is actively involved in time-domain surveys and the development of advanced algorithms for classifying and analyzing astronomical transients.

• Current Position: Assistant Professor of Astronomy
• Affiliation: Harvard University Center for Astrophysics

Her work integrates observational data from facilities like the Hubble Space Telescope (HST), James Webb Space Telescope (JWST), and the Vera C. Rubin Observatory to study supernova progenitors, explosion mechanisms, and circumstellar environments. Key research areas include pulsational pair instability models, binary progenitor systems, and the application of neural networks for rapid transient classification.

Dr. Villar has pioneered methods such as the SPLASH classifier, Superphot+, and Maven framework to enhance automated analysis of transient events. Her contributions to the Young Supernova Experiment (YSE) have resulted in large-scale datasets and photometric classifications of over 1,500 supernovae.

• Notable Projects: YSE DR1 Data Release, Rubin Observatory Target-of-Opportunity programs, LIGO/Virgo follow-up campaigns

Her research also addresses kilonova light-curve interpolation, gravitational wave follow-up strategies, and the detection of anomalies in variable star catalogs. She collaborates widely on multimessenger astronomy and next-generation survey strategies for transient detection.