Researchexominertransit detectiontess
NASA Model Identifies Thousands of Exoplanet Candidates
8.7
NASA scientists released ExoMiner++, an improved AI model that analyzed TESS data and identified about 7,000 possible exoplanets in its initial run. Trained on both Kepler and TESS labeled data and described in a paper in the Astronomical Journal, the model is available publicly on GitHub. Public release aims to accelerate exoplanet discovery and support future missions like the Roman Space Telescope.
Key Points
- 1Identifies 7,000 potential exoplanet transits from TESS data on initial run
- 2Trains on both Kepler and TESS labeled data, improving detection accuracy across surveys
- 3Publishes code on GitHub, enabling researchers and citizen scientists to independently search TESS
Scoring Rationale
Strong practical impact and peer-reviewed credibility, but the report provides limited methodological detail and initial candidate vetting.
Practice interview problems based on real data
1,625 SQL & Python problems across 15 industry datasets — the exact type of data you work with.
Try 250 free problems
