
A PhD-trained scientific programmer & GIS/AI Engineer
Thesis: Enhancing Soil Organic Carbon Estimation through Hyperspectral Dimensionality Reduction.
Awards: Summa Cum Laude and scholarship for academic excellence.
06/2025 – till date
Leading GIS and software development initiatives, delivering data-driven environmental and geospatial solutions using Python, remote sensing, and machine learning.
08/2022 – 05/2025
Developed machine learning–driven web applications, including semantic search systems and computer vision pipelines for real-world business workflows.
07/2008 – 04/2022
Led and architected full-stack development across diverse projects, from customised deployment platforms to enterprise billing systems.
Interactive GIS application development
Features: Cross-platform apps delivering interactive, user-friendly GIS layers
Skills: QGIS Server management, GIS data editing, GIS protocols, Bash scripting, mobile app development
Tools/Platforms: Ubuntu, Azure, Cursor IDE, Android Studio, Xcode, QGIS
Spectral index analysis and comparison system
Features: Interactive visualisation of spectral indices (NDVI, NDWI, etc.) across timelines with spatial point-based comparison
Skills: Remote sensing analysis, time-series processing, geospatial data handling, interactive visualisation
Tools/Platforms: Python, Google Earth Engine, React, AWS
ML system for vegetation classification
Features: Classification of native vs commercial vegetation
Skills: PyTorch model development, first-principles computer vision, pipeline design, data annotation strategy, training and evaluation protocols
Tools/Platforms: PyTorch, web-based interfaces for model testing
GIS reporting & spatial analytics
Features: Decision-ready spatial reports with precise filtering and validation
Skills: Spatial queries, spatial joins, overlay analysis, geoprocessing workflows, requirement interpretation, accuracy validation, automation with AI agents
Tools/Platforms: ArcGIS Pro, QGIS, Python, SQL, Claude