Starting Date: June 2026
Prerequisites: notion of data analysis and machine learning, python
Will results be assigned to University: No
Billions of exoplanets are orbiting around their stars outside our solar system [1]. Are they similar enough to our Earth so that life may have developed there? To answer this question, you need to know the planet’s mass, radius, and orbiting period. Given the astronomic distances between us and the planets, however, these quantities are estimated indirectly by fitting the Kepler equations to a series of sky observations.
In this project, you will use data from the Kepler mission [2], Neural Networks, and Conformal Predictors to infer various exoplanet parameters and classify them. Compared to the commonly used Bayesian approach [3], Neural Networks and Conformal Prediction can be scaled up to analyse datasets of millions of possible candidate planets.
[1] https://exoplanets.nasa.gov/, [2]https://exoplanetarchive.ipac.caltech.edu/docs/KeplerMission.html, [3]https://iopscience.iop.org/article/10.1086/432594/pdf, [4]https://www.jmlr.org/papers/volume9/shafer08a/shafer08a.pdf