Alongside my core research, I collaborate on applied projects that use data science and mathematical modeling to address real-world social challenges. Below are two recent examples.
In collaboration with music industry executive Emily White and the SNF Agora Institute at Johns Hopkins, I worked with a team of JHU undergraduates to build a data-driven tool for the #iVoted initiative — a campaign that leverages live concerts to boost voter registration and turnout.
The key insight driving the project: elections are often decided by margins the size of a concert venue. Our team built an interactive model that helps #iVoted identify which artists in each U.S. city could best mobilize low-propensity voters. The tool was used in the 2024 election cycle and continues to be utilized by the campaign.
This project was led by undergraduate students Tomoya Furutani, Jasmine Lafita, Jackson Shapiro, Cathy Wang, and Emi Hakutani.
In collaboration with Fadil Santosa and Yangxinyu Xie, I contributed to a simulation study analyzing the potential impact of Baltimore's proposed Red Line transit project on job accessibility across the city.
Combining transit and Census data, our model simulates how the 14-mile East-West rail line would change commute times and job accessibility for Baltimore residents — particularly those in mid-to-lower income communities on the city's east and west sides. Key findings include that an estimated 20% of workers in mid-to-low income jobs within the Red Line's service area would see a 50% increase in job accessibility, meaning they could reach work in 45 minutes or less.