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About me
I am a first-year PhD student focusing on improving flood mapping and natural disaster monitoring through the integration of remote sensing and artificial intelligence. My research explores how modern deep learning can improve Synthetic Aperture Radar (SAR) data value for flood mapping in complex urban environments.
Prior to my PhD, I completed an MSc in Artificial Intelligence and a BSc in Computer Science. Throughout my studies and research, I developed expertise in remote sensing, deep learning, and geospatial data analysis.
My dissertation project, “SAR to Optical Knowledge Transfer for Flood Segmentation”, investigated how knowledge learned from optical imagery can be transferred to radar data to improve flood mapping performance when optical observations are unavailable due to cloud cover or adverse weather conditions. This work combined deep learning, semantic segmentation, and multi-sensor Earth Observation data for disaster monitoring.
My interests include Earth Observation, artificial intelligence, computer vision, and the development of innovative solutions that transform complex data into meaningful information.
Outside of research, I enjoy programming, exploring new AI technologies, solving challenging technical problems, and continuously learning about emerging developments in technologies.