Jackson Ferrao

- Collaborating on ISPRS benchmar k on 3D point cloud to model registration (PC2Model) research project on simulation modelling of objects using LiDAR (Helios++) and Blender. - Executed 50+ object simulations to model point clouds, improved reproducibility. - Integrated add-on wor kflows into Blender, reducing scanner placement and execution time by more than 50% vs. command-line. - Processed and analysed 500+ 3D meshes, ensuring reproducibility and efficiency in large-scale simulations.

- Developed and implemented a scoring algorithm to analyse and rank unseen data, enhancing predictive capabilities. - Labelled and categorised 100+ files with 10,000+ records to ensure accurate and efficient data management. - Managed large datasets using MongoDB (NoSQL) and maintained data systems on Google Cloud, ensuring scalability, high availability, and reliable performance.

- Extracted and merged large-scale geospatial datasets (10GB+) from multiple APIs using Python (geopandas, rasterio, re quests), ensuring accurate integration across diverse sources. - Designed preprocessing wor kflows to clean, structure, and standardi z e geospatial data, enabling reproducible analysis and efficient visualization of spatial patterns and trends.

- Cleaned and integrated webinar data from 60+ campaigns using Power BI, Excel, and Pardot, improving lead conversion tracking accuracy by 20% - Created and maintained InfoHub training resources used by 40+ employees, reducing quer y resolution time by 70% - Designed user-friendly web forms that increased prospect acquisition by 10%