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Deployed Solutions.

Open-source tools, analytical dashboards, and modeling frameworks designed to solve specific geospatial logic problems.

Open Source & Tools
Python Library

PySpatialLag

A lightweight Python package for implementing Spatial Lag Models (SLM) on large datasets without the overhead of PySAL. Optimized for memory efficiency using sparse matrix operations.

Python NumPy Spatial Econometrics
Web Application

Huff Model Visualizer

An interactive React dashboard for calculating probabilistic trade areas based on the Huff Gravity Model. Allows users to adjust distance decay parameters (beta) in real-time.

React Mapbox GL JS D3.js
Microservice

Dockerized Isochrone API

A containerized service that generates drive-time polygons (isochrones) using OSRM. Designed for easy deployment on AWS ECS for scalable logistics planning.

Docker OSRM Node.js
Resources

R Spatial Templates

A curated collection of R scripts (using sf and tidyverse) for common GIS tasks: Point-in-Polygon, Nearest Neighbor, and Raster Reclassification.

R Tidyverse
Strategic Consulting
Chess leadership concept
Logistics Strategy

Global Supply Chain Resilience Audit

A comprehensive stress-testing framework designed for a Fortune 500 CPG client. We integrated climate risk data with tier-1 and tier-2 supplier locations to identify single points of failure.

Network Theory Risk Modeling
Client: Confidential (F500 CPG)
Abstract geometric background
Real Estate

Portfolio Valuation Model

Developed a bespoke spatial econometric model (Spatial Durbin) for an institutional REIT to value a $2B mixed-use portfolio, outperforming standard market appraisals by incorporating hyper-local connectivity metrics.

Spatial Econometrics R
Client: Institutional REIT
Modern minimalist architecture detail
Market Entry

Retail Expansion Strategy

Executed a gravity-based suitability analysis to identify 50 optimal locations for a UK-based retailer entering the US market, prioritizing proximity to competitor voids and target demographic clusters.

Suitability Analysis Python
Client: International Retailer