Raja Das is a geoscientist specializing in geospatial analytics, with a focus on using remote sensing, InSAR (Interferometric Synthetic Aperture Radar), and machine learning to detect, monitor, and model landslide hazards across diverse regions. His research combines satellite imagery and spatial analysis to understand where and why slope failures occur—particularly in data-scarce or landslide-prone regions. Originally from Kolkata, India, he earned his Ph.D. in Geospatial Analytics from North Carolina State University, after completing graduate degrees in Geosciences at East Tennessee State University and in Applied Geology at the University of Calcutta. His teaching emphasizes inquiry-based, hands-on learning and highlights the practical applications of geospatial tools in addressing environmental challenges. His work has been recognized with national awards and supported by organizations such as the Geological Society of America. He has presented his research internationally and published in peer-reviewed journals on topics including landslide susceptibility, risk modeling, and satellite-based hazard detection.