B.S. in Data Science Student Recognized for Transit Equity Research

Dailin Li, a second-year B.S. in Data Science student, was recognized at the University of Virginia’s Undergraduate Research Symposium for his work analyzing transit equity in Charlottesville. His research poster, titled “Temporal and Spatial Disparities in Bus Ridership: A Case Study of UVA- and Non-UVA-Affiliated Transit Services,” was recognized for its focus on equity-driven transportation planning.

The research project investigated how public bus usage differs between services operated for the UVA community and those serving the general public. Using tools such as ggplot for time-series analysis and Leaflet for interactive spatial mapping, Li explored two central questions: 1) when ridership peaks occur, and 2) where demand is most concentrated. His findings reveal sharp temporal peaks for UVA-affiliated routes clustered around class hours and campus locations, while non-affiliated services exhibit lower but more consistent usage patterns. Geographically, high ridership is seen near academic and commercial hubs, whereas several low-income neighborhoods show markedly limited access and frequency.

“The patterns suggest that UVA-affiliated routes are efficiently designed for student and staff mobility," said Li, though "there’s a real opportunity to expand non-UVA services in underserved areas."

With the support of his faculty advisor Prince Afriyie, Li's research uses data science to offer valuable insights for city planners and transit agencies. His research is a model of how undergraduate data science students can apply technical skills to solve real-world challenges and promote social good.