Priyanshu Diwan

Built a Sentinel-1/2 supervised crop classification workflow to map maize extent and demonstrate 5-year monocropping across a 20 km biochar feedstock sourcing area. Implemented dynamic baseline for VM0047 projects and conducted sea level rise impact analysis using pySLAMM for mangrove restoration projects.

Led multi-temporal satellite imagery analysis using Google Earth Engine, identifying over 1 million high-carbon potential land parcels across Brazil. Developed a web-based prospecting tool and created an AI chatbot using Python and LLM APIs to streamline carbon sequestration documentation.

Analyzed SMAP satellite data with Google Earth Engine to uncover plant available soil moisture variations across 732 districts of India. Used Google Colab to estimate soil moisture retention characteristics and visualized outputs with ENVI and QGIS.

Grade: 8.52/10

M.Tech. in Agricultural Systems and Management from Indian Institute of Technology, Kharagpur, completed in May 2024 with a CGPA of 8.52/10.

Grade: 7.90/10

B.Tech in Agricultural Engineering from Indira Gandhi Agricultural University, Raipur, completed in May 2022 with a CGPA of 7.90/10.

Grade: 66.7%

Completed Intermediate from Holy Cross Kapa, Raipur, in April 2018 with 66.7%.

Grade: 8.4/10

Completed Matriculation from Holy Cross Kapa, Raipur, in April 2016 with a CGPA of 8.4/10.

Completed Data Science with Python training from Acmegrade and IIT Bombay.

Completed Food Processing Training from Krishi Career Academy.

Completed Geospatial Analysis training from Kaggle.

Completed Farm Tractor & Machinery training from Smart Technical Centre.