Computer Vision for Ethnographic Research
My master's thesis - can a machine read a storefront? A computer vision pipeline that scans street view imagery for the languages and colors of storefront signage, and tests whether they can flag neighborhood demographic change before official data sees it.
Diversity in the United States
California's foreign-born share nearly doubled between 1980 and 2018, from 15% to 27% - but the national story is dispersal, not clustering. An interactive hex map of all 50 states plus DC, with national trends in education, languages, and citizenship.
Urban Mobility Index
An ML experiment predicting walkability from bus-stop and intersection densities across 774 neighborhoods in nine cities - and an honest account of where it works (the cities it trained on) and where it doesn't (the ones it hasn't seen).
Pedestrian Activity & San Francisco's Hills
Do San Francisco's steep blocks (≥20% grade) keep people from walking through them? We expected the hills to act as walls. The data pushed back: nearly a third of recorded trips crossed 'significant' slopes, and half of running trips did.
CitiBike Network Analysis
Summer ridership is 19x winter - and the network rewires itself with the seasons. Mapping 204K Citi Bike trips across Jersey City and Hoboken using Python, NetworkX, and Plotly.
Quality of Life of NYC Children
Most quality-of-life indices don't really account for kids. We built one that does - a 0–10 score for children across all 55 NYC PUMAs that combines infrastructure access, economic pressure, and environmental quality, framed by who actually lives in each district.
Got a Ride? Ridesharing Equity in Chicago
I expected Uber and Lyft pickups to cluster in white, wealthy Chicago neighborhoods. 42 million trips later, the data said no - the pickups go where the trips are, which mostly means downtown.