My research interests lie in leveraging machine learning and data science methodologies to analyze ice dynamics in polar glaciers and quantify their contributions to global sea-level rise using extensive satellite data archives. Throughout my PhD at the Bristol Glaciology Centre, I developed novel methodologies for mapping the grounding zone of the Antarctic Ice Sheet, utilizing data from the NASA ICESat-2 satellite. This research led to the development of the first ICESat-2-derived Antarctic Ice Sheet grounding zone data product, published in the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC). By using this new grounding zone product, I identified substantial retreats in the grounding lines of Moscow University and Totten Glacier ice shelves in East Antarctica over the past two decades. These findings have contributed to our understanding of the instability of the East Antarctic Ice Sheet and its potential impact on future sea-level rise. My involvement in this project also ignited a keen interest in deep learning techniques and their applications in polar glaciology. In 2022, I was awarded a PGR seed-corn research grant from the Jean-Golding Institute for my work on applying deep learning techniques to map the grounding zone using ICESat-2 data. Additionally, I was a visiting Research Fellow at the AI4EO Future Lab of the Technical University of Munich in Germany from February to April 2023, where I collaborated with leading AI experts in the field. Currently, I am a postdoctoral researcher on the EU Horizon 2020 project Arctic PASSION, aiming to establish a comprehensive and integrated pan-Arctic observing system.