I build practical computer vision, geospatial analytics, data engineering, and automation systems for real-world operations.
| Project | Focus | What it demonstrates |
|---|---|---|
| Rice Cultivar Vision Classifier | Agricultural computer vision | Grain segmentation, perspective alignment, and multi-class CNN inference with OpenCV and TensorFlow. |
| Distributed Satellite NDVI Pipeline | Remote sensing and GIS | Distributed parcel-level NDVI processing with Ray, Rasterio, PostGIS, and Power BI reporting. |
| DeepScanMap U-Net Segmentation | Deep learning | Patch-based semantic segmentation and reconstruction for ultra-high-resolution scanned maps. |
| NYC Mobility Geospatial Pipeline | Big data analytics | PySpark and Databricks ETL with reverse geocoding and Power BI mobility-flow analysis. |
| Python ETL Pipelines | Data engineering | PostgreSQL-to-MongoDB migration patterns and SQL Server transformations with upserts. |
| Object Vision | Interactive analytics | A React and TypeScript platform for real-time vector reduction and 3D similarity exploration. |
- Computer vision and deep learning for agriculture and industrial inspection
- Geospatial analytics, remote sensing, and spatial data pipelines
- Reliable ETL workflows, data transformation, and database integration
- Operational automation and decision-support visualizations
Python TensorFlow OpenCV PySpark Ray Rasterio PostGIS PostgreSQL MongoDB SQL Server Power BI React TypeScript
- RPA Sales Order Automation
- Tweet Sentiment Classification
- Medical Insurance Cost Prediction
- Student Happiness Predictor
I am especially interested in turning complex data, images, and operational workflows into systems people can use and trust.