Conducted a 2-hour live training with 140 registrants on using AI segmentation to delineate GIS features for hydraulic modeling, where attendees followed along on Python notebooks in the cloud. Three separate methods were taught for performing this delineation, depending on the use case.

This was prefaced by a live demo of these technologies with over 1000 people in attendance, which can be viewed in the above video.

Trained a custom fine-tuned deep learning building footprint detection model from satellite imagery, and built out a framework for it which allows the user to automatically detect and segment building footprints using AI remote sensing for an arbitrarily large area, and save the results back to a GIS shapefile. To accomplish this scalability, two separate spatial chunking, or "tiling" schemes were implemented, based on the respective optimal image resolution that the detection and segmentation models were each trained on. The tool is freely available, linked in the above image.