Zeinab Azarakhsh

Processed and analyzed 800+ large-scale satellite datasets to extract insights, identify long-term land deformation trends, and support data-driven decision-making for environmental research projects.

Estimated vertical land motion using 10-year satellite time series and InSAR techniques in the German Bight. Results presented at the SPP Sea Level Conference in Hamburg. Coordinated project activities and organized the international Sea Level Conference 2024. Managed the SPP 1889 project website and compiled final project reports.

Applied machine learning methods and time series analysis on large geospatial and satellite datasets to analyze trends and predict land subsidence. Built and validated predictive models to extract actionable insights from complex temporal data. Conducted research on radar remote sensing techniques for environmental applications. Co-authored a Persian technical book, Introduction to Radar Remote Sensing, published by Shahid Beheshti University Press (2021).

Completed a 12-week intensive Data Analytics Bootcamp focused on real-world business projects using Python, SQL, Tableau, and machine learning.