In 2023, Yoo & Lee proposed an alternate approach to bus route route design that optimizes for the connectivity of bus-dependent riders.
This brief paper provides a reinforcement-learning based implementation and evaluation on a selection of major U.S. cities using census and GTFS.
A study completed in August 2022 for the City of Oakland’s Department of Transportation (OakDOT). In response to citizen concerns about unequal allocation of parking enforcement resources, I created a combined dataset to evaluate the influence of demographic factors on citations issued in 2019.
Over 100 metrics, including racial makeup, income, education, 311 reports, road paving quality, home ownership, parking availability, and vehicle ownership were analyzed to determine their effect on enforcement.
Medium write-up and code samples for a Graph Neural Network model to predict bus delay times.
User research, data engineering, interface design, and final implementation for a tool to provide local journalists with NLP-assisted search, entity extraction, and topic-tracking against legislation, meeting minutes, and agendas from local municipalities. Final project for Stanford CS206: Computational Journalism.
Problem space exploration, user interviews, design evolution, and prototyping for a time management app, optimized for adults with ADHD. Final project for Stanford CS147: Human Computer Interaction Design.