Neethu Joseph

• Collect and preprocess satellite (Sentinel-2), climate, terrain, and soil texture data. • Develop SOC prediction models using Python and geospatial libraries. • Perform land cover classification using Sentinel data, spectral analysis, and the Segment Anything Model (SAM)

Designed and managed scalable datasets for thermosphere data analysis, focusing on trends and variations using Python and Pandas. • Developed ETL pipelines to process large volumes of satellite and model-generated data, ensuring data accuracy and quality. • Built data visualizations using Tableau and Matplotlib to support research and decision-making. • Collaborated with research teams to optimize data collection processes and align datasets with ML models for forecasting atmospheric trends.