MY RESEARCH WORK

In this research project in Astrophysics, spanning six weeks with a sizable team, I delved into the captivating realm of exoplanets and their potential moons. Immersed in tasks ranging from data collection to Python script analysis, research writing, and presentations, I honed essential skills crucial for graduate school pursuits. Focused on uncovering exomoons using gravitational effects on exoplanets, our work aimed to detect subtle signals beyond the reach of direct observation. Leveraging data from missions like Kepler, we explored Transit Timing Variations (TTV), Transit Duration Variations (TDV), and Transit Photometric Variations (TPV) to unearth potential exomoon candidates. Despite the absence of concrete evidence to date, our research contributed to the burgeoning field of exomoon exploration, driven by the promise of expanding our understanding of habitable conditions beyond our solar system.

During my research internship under Asst. Prof. Dr. Ugemuge I  employed machine learning techniques in the analysis of Kepler time series data. Leveraging my expertise, I developed a classification model utilizing Logistic Regression and Decision Tree Classifier algorithms to predict whether a star has an orbiting exoplanet based on Kepler time series data. Achieving an impressive 98% validation accuracy and weighted F1-score, this project significantly bolstered my proficiency in machine learning accuracy techniques, marking a notable advancement in my skill set.