He aspires to become an expert in hydroinformatics, specializing in handling and processing various types of data in the field of hydrology. His primary interest lies in developing image-based rainfall estimation algorithms that have the potential to replace traditional observation devices. Additionally, he is focused on creating fusion algorithms for hydrological and meteorological data, particularly in the integration of remote sensing data and numerical weather prediction models using machine learning techniques. His goal is to efficiently extract and utilize the features of these datasets. In the future, he aims to contribute to the digital-twin domain by merging and analyzing large-scale hydrological and meteorological datasets. Ultimately, he hopes to play a role as a technician who supports the resolution of broader societal challenges through advanced data analysis and integration.