Sourav Bhadra is a data scientist specializing in remote sensing, computer vision, and geospatial machine learning for AgTech, with eight years of experience bridging research and production at organizations like Bayer and Saint Louis University. He builds open-source Python tools (notably Raster4ML and MapLapse) and has a strong track record of fusing multisensor UAV and satellite data—combining 2D/3D CNNs, transfer learning, and cloud scaling on AWS SageMaker—to solve crop phenotyping and yield prediction problems. His work spans the full pipeline from automated UAV data collection and preprocessing to model deployment and interactive web mapping, and he has taught graduate courses on geospatial analytics. A PhD candidate in Geoinformatics, Sourav pairs rigorous academic methods (e.g., radiative transfer hybridization, voxelized LiDAR 3D CNNs) with practical engineering, including a recent pivot into web-based apps and cloud deployments that makes his research readily reusable.
8 years of coding experience
4 years of employment as a software developer
Bachelor, Urban and Regional Planning, Bachelor, Urban and Regional Planning at Khulna University of Engineering and Technology
Doctor of Philosophy - PhD, GeoInformatics and Geospatial Analytics, Doctor of Philosophy - PhD, GeoInformatics and Geospatial Analytics at Saint Louis University
MSc, Geography and Environmental Resources, MSc, Geography and Environmental Resources at Southern Illinois University, Carbondale
Codes to calculate solar-sensor zenith and azimuth angles directly from hyperspectral images collected by UAV. Works only for UAVs that have high resolution GNSS/IMU unit.
Contributions:21 commits in 1 day
anglesimuazimuthazimuth-anglessolar
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