TerraIO
Geotechnical Engineer | Point Cloud Analysis | Data Visualization
Welcome
I am a geotechnical engineer with a passion for leveraging advanced data analysis techniques to solve complex engineering challenges. My work focuses on point cloud data processing and creating intuitive web and desktop applications for large-scale data visualization.
Through my work, I bridge the gap between traditional geotechnical engineering and modern data science, developing tools that make complex spatial data accessible and actionable for engineering decision-making.
Expertise Overview
Geotechnical Engineering
- Underground modellling
- Stope analysis
- Underground QAQC
- Ground improvement techniques
- Core logging
Point Cloud Analysis
- LiDAR data processing
- 3D terrain modeling
- Feature extraction & classification
- Change detection analysis
- Volumetric calculations
Data Visualization
- Interactive web/desktop applications
- 3D visualization (Three.js, WebGL)
- Real-time dashboards
- Geospatial mapping
- Custom visualization tools
Technical Stack
- Python, JavaScript, R
- React, D3.js, Plotly
- CloudCompare, PDAL
- GIS software & libraries
- Machine learning & AI
Featured Projects
Web-based interactive point cloud data illustration
This project showcases an underground tunnel point cloud delivered as a seamless, web-based walkthrough. The focus is on optimised data hosting and intuitive online visualisation, enabling teams to explore complex underground spaces remotely without specialised software.
View live demo hereInteractive Web-Based Geospatial Mapping
This project presents an interactive web-based map developed using Python (Folium), focusing on efficient data handling and intuitive online visualisation. Due to data sensitivity, the video demonstration is not publicly displayed; comparable examples can be provided upon request.
Desktop 3D Data Visualisation & Analysis
A desktop-based application developed in Python using VTK for advanced visualisation and analysis of meshes and point clouds. The tool supports operations such as region growing, normal vector estimation, and feature classification to enable efficient interpretation of complex 3D datasets.