Selected projects, public tools and research materials.
Published:
Developed a model for forecasting revenue and selecting a retail chain scaling strategy: compared unified and separate models for different store formats, identified key drivers, and formulated an approach to ranking “location × format × product assortment × operating hours” scenarios.
Published:
Developed three sales forecasting scenarios across 12 product categories based on time series and linear regression applied to historical data with controlled error, which enabled the automation of the ETL data processing pipeline. Databricks, Scikit-learn.
Published:
Planter is a spatial planning tool for exploring industrial facility locations and regional labour flows. It identifies nearby cities within a travel-time radius, incorporates workforce requirements, and explores how changes in urban quality of life and salaries affect predicted migration and regional flows.
Published:
Improved the method for estimating the population of each building in the city by reconstructing missing data on building heights with an accuracy of one floor and an error of less than 15% using a decision tree and spatial autocorrelation. Scikit-learn, PySAL, OSMnx, Jenkspy.
Published:
Assessed changes in the load on social infrastructure by developing a method to calculate the N-minute accessibility of areas, taking into account future development; applied this approach to the planning of clinics, schools, and other social facilities.
Published:
Geocoded map of laboratories, centers, schools, and research groups related to geospatial, urban, spatial, environment, architecture, and transport topics.
Published:
Tools for building review tabs in Google Sheets, finding conference-year evidence, and supporting human verification.
Published:
Extracts characters, places, and movements from books using AI and visualizes them as an interactive spatial graph.
Work in progress
Work in progress: classifying urban blocks by dominant land use from urban spatial data.