PhD student wins 3rd place in competitive data challenge!
researchTDE
My PhD student Sigrid Nissen achieved a fantastic result by finishing 3rd out of 895 participants in the MALLORN Astronomical Classification Challenge, a public data challenge hosted on Kaggle!
The goal of the challenge was to develop machine-learning algorithms capable of identifying Tidal Disruption Events (stars being torn apart by black holes) within the enormous data stream expected from the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), using simulated light curves.
Many congratulations to Sigrid! I am looking forward to applying these methods on the real LSST data and find real TDEs!