Jyoti Singh

Maintain and enrich the fiber GIS database for network planning and operational decisions. Run fiber pair feasibility checks and manage cluster-level fiber data, including OFC KMZ files and topology updates.

Built and maintained automated CWIP POP dashboards covering around 26,000 sites. Automated GIS workflows in Python, reducing a two-day job to about three hours.

Planned intercity and intracity fiber routes to extend network coverage. Wrote Python scripts to replace slow manual spatial queries and supported transport planning through node identification.

Mapped Kharif crops using SAR satellite data and machine learning models built in Python. Pre-processed SAR satellite images and trained machine learning classifiers for crop classification.

Mapped trees outside forests and agroforestry systems using Sentinel-2 and high-resolution imagery with AI. Compared Random Forest, SVM, and U-Net models for pixel-level mapping, with U-Net achieving the highest accuracy.

Post Graduate Diploma in Data Science and Business Analytics from Great Learning, Delhi, India, from 2022 to 2023.

Grade: CGPA 7.15

MSc in Geo-Informatics from TERI School of Advanced Studies, Delhi, India, from 2020 to 2022, with a CGPA of 7.15.

Grade: CGPA 6.93, First Division

BA (Honours) in Geography from the University of Delhi, Delhi, India, from 2017 to 2020, with a CGPA of 6.93 and First Division.

Grade: 75.8%

Completed Class XII from Kendriya Vidyalaya, BSF Camp Chhawla, Delhi, India, in 2017, with 75.8%.