ExoSeeker is an end-to-end Artificial Intelligence platform designed to accelerate the discovery of exoplanets.
It unifies heterogeneous datasets from NASA missions Kepler, K2, and TESS, applying Explainable AI for robust and transparent classifications.
This is the official video presentation of the ExoSeeker project for the NASA Space Apps Challenge:
This is the official site of the ExoSeeker project for the NASA Space Apps Challenge:
ExoSeeker automates the classification of exoplanet candidates.
We tested multiple models: Decision Tree, KNN, Naive Bayes, Random Forest, LightGBM, and 1D-CNN, prioritizing F1-score as the main metric.
Key features:
✅ Consolidates data from NASA catalogs
✅ Balances and cleans datasets
✅ Uses Explainable AI (SHAP + Grad-CAM)
✅ Provides web interface for analysis & PDF reports
✅ Open-source, reproducible, and globally accessible
ExoSeeker addresses one of astronomy’s greatest challenges:
the exponential growth of exoplanet data that still requires time-consuming human validation.
- Languages & Frameworks: Python, PyTorch/Lightning, LightGBM
- Optimization: Optuna (hyperparameter tuning)
- Web Stack: FastAPI, Next.js, Plotly
- Data Storage: PostgreSQL, Redis
- Reproducibility: conda-lock environments, fixed seeds
- Data Pipeline → Ingests Kepler, K2, and TESS datasets.
- Training → Runs multiple ML models for robust classification.
- Explainability → SHAP + Grad-CAM show why a signal is labeled as a planet.
- Interface → Upload data, run analysis, view metrics, download PDF reports.
AI was the core of this project:
- Classification: ML models detect planets vs. false positives.
- Evaluation: Balanced datasets, hyperparameter tuning, F1-score optimization.
- Explainability: SHAP & Grad-CAM for transparency.
- Integration: Web interface connects models to user workflows.
Acknowledgment of AI Use
- All AI outputs are documented and labeled.
- No NASA logos or branding were used.
- Any illustrative AI-generated media includes watermarks.
| Name | Country | Role |
|---|---|---|
| Marina Corrêa Freitas ⭐ (Team Owner) | 🇧🇷 Brazil | 🚀 Project Lead |
| Luiza Arievilo | 🇧🇷 Brazil | 🔬 Research |
| Márcia Saori Câmara Kishi | 🇧🇷 Brazil | 🎨 Research & Design |
| Jannaina Anita Sangaletti | 🇧🇷 Brazil | 🤖 Machine Learning & Data |
| Samantha Nunes | 🇧🇷 Brazil | 💻 Frontend & UX |
| Barbara Lais Dorneles Martins | 🇧🇷 Brazil | 🔧 Backend & Integration |
✨ ExoSeeker accelerates exoplanet discovery and makes science transparent, reliable, and open to all.