BlackEye is an AI system that processes NASA's Kepler and TESS datasets to identify and characterize exoplanets through a smart approach. The system analyzes 17,232 space objects using 12 basic features plus 3 physics-based smart calculated features, then uses AI to find planets and predict their physical properties.
To democratize universe exploration through AI by creating a unified system that processes NASA's Kepler and TESS data to identify and characterize distant worlds with scientific rigor. BlackEye accelerates universe observation by providing researchers with powerful, automatic analysis tools that can process NASA's massive datasets in real-time.
To inspire the next generation of space explorers by developing a robust, scientifically-validated universe observation system that serves as a foundation for future astronomical research and contributes to our understanding of planetary systems beyond our solar system. BlackEye advances our understanding of planetary systems by making NASA data more accessible to everyone, supporting ongoing NASA missions and future space telescope operations.
Unlike traditional approaches that separate planet detection and property prediction, BlackEye handles both tasks simultaneously, providing comprehensive exoplanet characterization in a single framework. The system unifies data from multiple NASA missions into a single analysis framework, enabling researchers to process thousands of candidates efficiently while maintaining scientific rigor.
BlackEye incorporates physics-based smart calculations with custom features based on astronomical principles. The system uses 12 basic features plus 3 smart calculated features (period_to_duration_ratio, depth_to_mag_ratio, error_quality_score) for better model performance and cross-mission compatibility. Learn more about our AI technology →
BlackEye is based on peer-reviewed methodology and established astronomical practices. The system provides comprehensive validation with cross-validation and performance metrics, uncertainty quantification with confidence estimates for all predictions, and reproducible results through open-source implementation with detailed documentation. View performance details →
BlackEye features modular architecture with clean separation of concerns, scalable design that handles large datasets efficiently, Docker support for easy deployment and reproducibility, API-first design for integration with existing research workflows, and comprehensive customization options for all AI models.
BlackEye employs a smart approach that combines planet detection and property prediction to provide comprehensive exoplanet analysis. The system simultaneously finds planets as CONFIRMED, CANDIDATE, FALSE_POSITIVE, or UNKNOWN while predicting 7 key scientific measurements including orbital period, planet radius, equilibrium temperature, and stellar properties. Explore parameter predictions →
BlackEye provides comprehensive customization options for all AI models, allowing researchers to customize classifier, planet regressor, stellar regressor, and quality regressor measurements for optimal performance. The system includes configurable AI parameters (learning rate, max depth, n_estimators, subsample, colsample_bytree) and custom model training capabilities for researcher-specific measurement configuration.
A passionate group of scientists and engineers working together to advance universe observation through cutting-edge AI technology.
Team Lead & AI/ML Engineer
Leading the team and developing AI models for universe observation. Expert in deep learning, model training, smart calculations, and AI approach optimization for astronomical data analysis.
Frontend Developer
Building responsive and interactive user interfaces for the BlackEye platform. Expert in modern JavaScript frameworks, React, responsive design, and creating intuitive web experiences for data visualization.
Hardware Engineer
Designing and implementing hardware solutions for space observation systems. Expert in embedded systems, sensor integration, and building reliable hardware for astronomical data collection.
Hardware Engineer
Developing advanced hardware components for universe observation platforms. Expert in electronics design, signal processing, and creating robust systems for space exploration technology.
Researcher
Conducting research on exoplanet discovery and universe observation techniques. Expert in astronomical data analysis, scientific methodology, and advancing our understanding of planetary systems.