"Precision is not just a metric. It is the mindset that shapes every spatial decision."

I do not wait for problems to be assigned. I find them, understand why they exist, build the fix, and ship it to production. At AiDash I was the fastest analyst to reach live deployment on a major client engagement, not because I worked faster but because I understood the full problem before writing a single line.

Most GIS engineers at the 2 to 4 year level execute workflows. I build the tools that make workflows obsolete.

My approach: when something takes 10 minutes and it should take 60 seconds, I do not accept it as a constraint. I write the Python to collapse it. When accuracy fails in the field, I trace it back to the source, whether that is spectral overlap, angle variation, or logic gaps in the QC tool, and I fix the root cause rather than the symptom.

That is why I was selected exclusively for field validation feeders requiring zero error tolerance. And why a hackathon project I built in one day processed 1 million hectares in under 9 minutes.

Production QGIS automation models, satellite imagery pipelines, habitat classification workflows, and tree health quality control systems built for real client deployments. Every model in this repo replaced a manual process that was creating errors or consuming disproportionate time.

Domains covered: electrical utility vegetation management, UK Biodiversity Net Gain, coastal habitat annotation, urban ecosystem mapping

Rule-based BNG habitat classification engine built at the AiDash Hackathon 2025. Processes habitat polygons against Defra Biodiversity Metric 4.0 SOP logic across England, Scotland, and Wales. The build that achieved 1 million hectares in under 9 minutes and compressed per-site turnaround from 20 minutes to 4 minutes.

The plugin that eliminated manual satellite image sourcing entirely. Parametric AOI generation, dynamic 235-ft buffer logic, and cloud-threshold filtering in a single production-grade Python workflow. Built because the manual process had no version control, no repeatability, and no error handling.

Mangrove, seagrass, coral reef, and saltmarsh delineation from multispectral Sentinel imagery for supervised ML pipelines. UAE field project. Produced 12 QA-verified habitat classes across 3 coastal zones as the labelled foundation for an operational classification model.

GIS platforms

QGIS, ArcGIS Pro, GDAL/OGR, PostGIS, Google Earth Engine, AIMS

Programming and automation

Python, PyQGIS, GeoPandas, Rasterio, Shapely, NumPy, Pandas, SQL, JavaScript

AI and machine learning

SAM (Segment Anything Model), YOLOv8, TensorFlow, PyTorch, Random Forest, XGBoost

Satellite and imagery

Sentinel-2, Landsat 8/9, MODIS, GSAT, Aerial (5 to 50 cm), NDVI/EVI/SAVI, OBIA

Databases and cloud

PostgreSQL, PostGIS, AWS, GCP, Docker, Git, REST APIs

Domain standards

UK BNG Legislation, Defra Biodiversity Metric 4.0, UKHab Classification, OGC Standards, T&D Utility Workflows

Working with IVMS (Intelligent Vegetation Management System) and AIMS (Asset Inspection and Monitoring System) on live T&D infrastructure at scale. Tree species detection across 14,600 line miles, tree health QA with 94.04% field-validated accuracy, vegetation encroachment classification, satellite imagery co-registration, and span-level automation. All delivered under direct client accountability with field validation against ground truth.

Built automation for the BNG AI product covering Defra Biodiversity Metric 4.0 classification across Britain. UKHab classification, habitat polygon labelling at scale, rule-based SOP automation, and the Code4Habitat platform that set a throughput benchmark of 1 million hectares in under 9 minutes at the 2025 internal hackathon.

M.Sc. Geology, University of Madras, Chennai (2021 to 2023). RUSA Project Fellow. Funded research in sedimentology and trace element geochemistry for environmental impact assessment.

B.Sc. Geology, National College, Tiruchirappalli (2018 to 2021). Elected Climate Resilience Head.

Certifications: Geospatial Technology FOSS4G at IIRS and ISRO, Remote Sensing and GIS for Meteorological Hazards at NIDM, FOSSEE Mapathon at IIT Bombay, Nature-Based Solutions at NIDM.

Senior GIS Engineer, Geospatial AI Engineer, Remote Sensing Engineer, Spatial Data Engineer, GIS Automation Lead. Target roles in geospatial AI, environmental technology, smart infrastructure, biodiversity compliance, or utility asset management.

If you are hiring for someone who brings a problem-solving mindset, builds tools that did not exist before, and raises the accuracy bar on every project they touch, let us talk.