Niharika Sravan
Papers
1
Total Citations
5
H-Index
1
About
Niharika Sravan is a leading figure in time-domain astrophysics, specializing in the classification and physical characterization of core-collapse supernovae. Her research bridges observational astronomy and machine learning, with a focus on developing automated tools to handle the deluge of transient data from modern sky surveys. Sravan’s most notable contribution is the creation of **CCSNscore**, a multi-input deep learning tool that rapidly classifies core-collapse supernovae using spectra from the SED-machine instrument. This work, already garnering early citations, addresses a critical bottleneck in supernova science: the need for real-time, accurate classification amid the thousands of candidates discovered nightly by surveys like the Zwicky Transient Facility (ZTF). By enabling faster identification of core-collapse events, her tool paves the way for prompt follow-up observations and deeper studies of stellar death. Sravan’s impact is amplified by her role in the broader transient community, where she advocates for open-source, scalable solutions. Her contributions are essential as astronomy enters an era of unprecedented discovery rates, ensuring that every supernova—not just the brightest—can be studied in detail.
Research Focus
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Top Papers
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