kumar shivam

I work at the intersection of geospatial analytics, AI, and catastrophe-risk engineering. Over the past eight years, I’ve built large-scale exposure datasets, designed deep-learning models for satellite-image intelligence, and developed R&D systems that support global insurance and risk platforms. My experience includes building footprint extraction, roof-type classification, geocoding engines, event-loss prediction tools, and hazard-data integrations using Python, PyTorch, FastAPI, QGIS, PostGIS, and Databricks.

My academic background in geoinformatics and remote sensing from NIT Bhopal and research exposure at IISc Bangalore allow me to combine scientific rigor with practical engineering. I enjoy solving complex spatial problems and creating end-to-end solutions that turn raw data into clear, actionable insights.

Your education sits like a neat geological core sample of how you became who you are. You started with a B.Tech in Civil Engineering at MS Ramaiah, where you dipped into water resources, irrigation studies, and the gritty realities of soil and land. That curiosity pulled you toward the invisible wavelengths above us, so you moved into an M.Tech in Geoinformatics at NIT Bhopal—ranked near the top of your class—where remote sensing, satellite imagery, machine learning, and spatial analytics became your playground.

During your M.Tech, you spent time at IISc Bangalore as an intern, absorbing the physics of microwave remote sensing and learning how to coax meaning out of complex radiometric data. Each step sharpened your ability to blend engineering logic with Earth observation science, setting the stage for your later work in geospatial AI.