Projects

Problem

Manual RFP searching required analysts to spend months reviewing thousands of government contracts to find relevant fiber and telecom opportunities.

Solution

Built a production desktop application using Azure OpenAI (GPT-5.1) and Google AI Studio to automate web grounding, intelligent classification, and matching of RFPs to company capabilities. Features batch search, URL validation, and CSV export.

Impact

• Processing time reduced from months to hours
• Automated classification of thousands of contracts
• Deployed as a production tool at Olsson

Problem

Identifying utility poles, streetlights, and telecom infrastructure in aerial imagery required expensive manual inspection across large geographic areas.

Solution

Built a desktop application that fetches high-resolution aerial tiles by coordinate, runs a custom-trained YOLO model to detect utility assets, and exports georeferenced results to ArcGIS. Supports single-point, grid, and area scanning modes with tile navigation controls.

Impact

• Automated detection of utility poles and streetlights from aerial tiles
• Georeferenced export to GIS-ready formats
• Custom YOLO model trained on telecom infrastructure classes

Problem

Field surveys for utility poles and telecom equipment require costly in-person visits, and traditional GIS methods cannot identify specific physical assets from ground level.

Solution

Built a desktop application that traverses streets using street-level imagery, running a custom YOLO model to detect and classify utility infrastructure. Supports line traversal, panoramic capture, and area buffering with step-by-step navigation controls.

Impact

• Remote field survey capability without site visits
• Automated inventory of streetside utility assets
• Configurable traversal distance and panoramic heading coverage

Problem

Generating bore profiles for fiber network directional drilling required days of manual drafting, creating bottlenecks in project timelines and introducing human error.

Solution

Developed a fully automated desktop application that reads spatial waypoints from an interactive map, processes elevation models, calculates bore depth and slope, and generates production-ready 2D and 3D elevation profiles with configurable running lines and break points.

Impact

• Processing time cut from days to minutes
• Eliminated manual drafting errors
• Deployed across the telecom engineering team at Olsson

Problem

Complex fiber network design workflows required repetitive manual GIS operations, slowing down engineers and creating inconsistencies across projects.

Solution

Developed a suite of custom Python geoprocessing toolboxes for ArcGIS Pro that automate routing analysis, cost estimation, and network design workflows.

Impact

• 90% reduction in manual processing steps
• Accelerated fiber network design timelines
• Improved cost estimation accuracy

Problem

Limited understanding of spatiotemporal patterns of NOx emissions from U.S. cement plants and their environmental justice implications.

Solution

Used TROPOMI satellite data to perform spatiotemporal hotspot analysis of NOx emissions, correlating emission patterns with population demographics and environmental justice indicators.

Impact

• Full MS thesis — GPA 4.00
• Remote sensing analysis of all U.S. cement plants
• Environmental justice exposure analysis for affected populations

Problem

Historical patterns of racial exclusion in Omaha real estate were undocumented spatially, making it difficult to understand the geographic scope of discriminatory practices.

Solution

Digitized historical land parcels from archival documents and aerial photography, georeferenced historical maps, and built a spatial database revealing redlining and racial covenant patterns.

Impact

• Revealed spatial patterns of racial exclusion
• Contributed to urban spatial justice research
• Accurate historical parcel database for Omaha