Full-stack AI system combining physics-based validation and a hybrid CNN-Transformer to classify exoplanets from NASA Kepler light curves.

A focus on the relationships between stellar characteristics, their classification, and the properties of their orbiting planets.

An Exoplanet parser developed using Node JS which parses exoplanets based on some parameters from the planets data collected by Nasa's Kepler Telescope

Predicting exoplanets using ML models trained on Kepler data

This repo contains the code I used to study the habitability index ESI and SEPHI for 3 exoplanets.

Using machine learning techniques with Kepler Space Telescope exoplanet search data to train and tune classification models

🚀 A little space-exploration using Deno

🌟 AI-powered exoplanet detection system using NASA data for Space Apps 2025 hackathon. Features BLS/TLS algorithms, machine learning classification, and real-time analysis pipeline. | 使用 NASA 資料的 AI 系外行星偵測系統，專為 2025 太空應用程式挑戰賽開發。

Are we alone in the universe? Is there life beyond earth? This project explores these questions using NASA's Kepler telescope data

Modelo de Aprendizado Profundo para identificação de Exoplaneta em dado do Telescópio Espacial Kepler.

The StarScope project implements a one-dimensional convolutional neural network (CNN) from scratch in NumPy and evaluates its ability to detect exoplanets from labeled Kepler Space Telescope light curve data. Labeled data is from the Exoplanet Hunting in Deep Space dataset, by WΔ.