AI tool developed at Oxford helps astronomers find supernovae in a sky full of noise
Peer-Reviewed Publication
Updates every hour. Last Updated: 21-Nov-2025 09:11 ET (21-Nov-2025 14:11 GMT/UTC)
A new AI-powered tool has reduced astronomers’ workload by 85% - filtering through thousands of data alerts to identify the few genuine signals caused by supernovae (powerful explosions from dying stars). The findings have been published today (10 Sept) in The Astrophysical Journal.
Researchers led by Noah Cowan at Johns Hopkins University have secured NIH funding to probe how animals alternate between "explore" (sensing) and "exploit" (task-oriented) behaviors in uncertain environments, using the weakly electric glass knifefish as a model. The team includes researchers from four universities who will integrate their expertise in neuroscience, math, engineering, and machine learning to build on 2023 findings in Nature Machine Intelligence that revealed the explore/exploit pattern across species from amoebas to humans. The project aims to decode decision triggers, with implications for robotics and medicine.