Exoplanet Data Analysis
Self-taught exoplanet hunting: 800+ TESS light curves classified by hand, then the same job done in Python against Kepler data.
Analysed 800+ TESS satellite light curves on Zooniverse’s Planet Hunters, then moved from classifying transits by eye to writing the analysis directly — using Python on open-source Kepler data to detect possible exoplanets and characterise their properties.
Learned the working data-analysis stack along the way — NumPy, Matplotlib, pandas and scikit-learn — self-taught through Kaggle, Udacity, freeCodeCamp and Codexio.
What it led to
- IAAC — this independent project was the only preparation available before the International Astronomy and Astrophysics Competition, which went on to a National Award and international Bronze.
- Follow-on work — the habitability question raised here became a dedicated research group, now studying whether the Earth Similarity Index is systematically biased.