I am a Dynamic Data Scientist and Earth Observation Specialist with 4+ years of experience in Machine Learning, Deep Learning, LLMs, Computer Vision, and satellite analytics. I specialize in Multispectral, SAR, and optical imagery, with strong expertise in data pipelines, production deployment, and AI-driven solutions.
I work as a Satellite Data Analysis Engineer at Solafune Inc. in Tokyo, Japan, where I research and develop technologies for satellite and geospatial data analysis. My day-to-day work involves processing Earth Observation datasets, including Synthetic Aperture Radar (SAR) imagery, to analyze ground deformation from seismic activity and support early detection of earthquake-related surface changes. I also apply AI and machine learning techniques to extract insights from large-scale geospatial data for applications such as flood monitoring, drought assessment, and natural hazard analysis.
My academic foundation is an M.Tech in Geoinformatics and Natural Resources Engineering from IIT Bombay, where I researched glacier classification using SAR data and machine learning. Before joining Solafune, I worked at Rakuten in Japan, where I built ML-based customer churn prediction models, developed anomaly detection systems for 5G network operations, and managed over 1600 RAN clusters across 25+ cities, saving approximately 4 million yen per year in operational costs.
I believe the next frontier of humanitarian resilience lies in open, operational Earth Observation pipelines that make space-derived intelligence accessible to the communities that need it most.
Open to collaborations in geospatial AI,
climate risk, and satellite data research.