Andrew
Ding.

Educational

Master of Science ETH in Data Science
Bachelor of Environmental Studies
Cumulative Average: 96.3%

Diploma of Excellence in Geographic Information Systems and Certificate in Global Experience.


Professional

Currently working on the Digital Twin of Switzerland project.
Adapted a Markov chain model by overhauling the process of training and validating transition matrices. These matrices forecast customer charge-off rates by predicting future delinquency progression over several statements.
Designed and developed interactive web applications using Mapbox GL JS and Turf.js, empowering both clients and colleagues to make data-driven decisions through easy-to-use spatial analysis tools.
Streamlined transit reach modeling and analysis efforts by developing an automation script that converts GTFS files into a Network Dataset, resulting in more efficient and accurate transit network analysis.
Conducted in-depth exploratory spatial analysis using R and various packages such as sf, raster, and ggplot, utilizing a combination of raster and microdata to analyze demographic trends over different temporal periods.
Developed a methodology to categorize and assign sets of census polygons to functional urban areas in developing countries, resulting in a more accurate representation of demographic data, to be used in a future research publication.
Developed efficient workflows and methods using ArcGIS Pro to automate the identification and removal of extraneous line segments, reducing the runtime of water distribution model simulations and improving overall performance.
Conducted data analysis using Python to compare and validate the accuracy of predicted discharge flow against calculated discharge flow, as well as identify deviations in discharge flow during water break events.
Created multiple geoprocessing tools using ArcGIS ModelBuilder to streamline the analysis of vector features, and incorporated the results into an interactive dashboard using PowerBI for easy visualization and interpretation.
Utilized NDVI and EVI rasters, accessed through NASA Earthdata, to assess vegetation levels in the wintering ranges of migratory birds. This research was published, providing valuable insights on the habitats of these species.
Refined and deployed an interactive walking tour webapp using ArcGIS Webapp Builder and ArcGIS Online, providing users with a dynamic and engaging way to explore a given historical interest.