Research &
Projects
A full overview of research, data engineering, geovisualization, and spatial analysis projects — from peer-reviewed publications to interactive web maps.
Developed a multi-step framework to resolve unstructured birthplace text in crowd-sourced genealogical data. Combined hierarchical geographic matching with LLM-based validation and human-in-the-loop correction to geocode 25+ million records from the 1850–1920 period.
Built Python + PostGIS pipelines to clean and process 280M historical place records, constructing a 60M-node spatial network. Used community detection and network analysis to map migration regions and compare family tree data with linked census records.
Building a spatial-social network dataset from a large crowd-sourced historical family tree to study how sibling and sibling-in-law ties shaped migration patterns and community structure in the 19th-century United States.
Developed an NSF-funded interactive story map for the BluGAP project to communicate river water-quality risk assessments to watershed communities. Designed visual narratives showing how pollution travels downstream and concentrates in vulnerable areas.
Created an animated D3.js map illustrating Iowa's changing population density over time, tracing the gradual shift from river-dominated landscapes to those shaped by railroads and major roads — showing how transportation infrastructure shaped settlement.
A collection of interactive maps built in D3.js and Observable, including choropleth maps of 1920 US population, graduated symbol maps, bivariate maps, isarithmic maps, and flow maps illustrating migration patterns.
Analyzed how COVID-19 disrupted spatial and social interaction networks, quantifying structural changes in communication and mobility patterns before and after the pandemic using network analysis methods.
Interactive web map comparing community detection algorithms for identifying migration regions in the United States from historical family tree data. Includes small-multiple maps and dynamic algorithm comparisons.
Developed GIS-based DRASTIC models integrated with evolutionary algorithms (genetic algorithm, particle swarm optimization) and multi-criteria decision-making methods to assess groundwater vulnerability and nitrate contamination risk in multiple aquifer systems.
Developed and evaluated two automated Python solutions for mapping changes in spatial communities over time, using GeoPandas and graph-based methods to detect and visualize shifting regional boundaries in migration networks.
Explored connections between countries, regions, and continents in merchandise and service trade networks before and after the COVID-19 pandemic as part of the NSF-funded I-GUIDE Summer School. Results presented at the I-GUIDE Virtual Consulting Office.