Predict the profitability of potential coffee shop locations using SQL and Python. Combines data engineering with feature-rich regression modeling, visual analytics, and business insights to support data-driven site selection and retail decision-making.

KnowSite: Leveraging Urban Knowledge Graph for Site Selection

Public charging station utilization dataset for the city of Hamburg. Dataset is described in the respective paper: Placing BEV Charging Infrastructure: Influencing Factors, Metrics, and their Influence on Observed Charger Utilization

Coco provides a fast, exact method to solve variations of the Reserve Selection problem including connectivity. It provides a python implementation using the Gurobi ILP solver

Interactive Streamlit app using ML and geospatial analysis to prioritize EV charging station locations

⚗️ A repository for open and community driven case studies using the Dotlas API, curated by Dotlas

This project analyzes restaurant site selection in Cambridge by examining human mobility patterns, street network centrality, and land use. Using check-in data from Gowalla and OSMnx for street network and land-use mapping, it identifies optimal restaurant locations. The study prioritizes accessibility to maximize foot traffic and profitability.

A multi-criteria decision analysis (MCDA)-based composite proxy target variable generation technique for business decision modeling that uses relevant features or independent variables conceptually related to the intended target variable.

String matching with regrex to extract Nevada site selection factors

A platform for supporting onshore wind farm siting in Australia

Sports/Leisure Centre Site Selection with ArcGIS Raster Analysis