Anita Chen

Chen’s own professional account describes a 2021 thesis on recoil in viscoelastic materials, earlier work on algorithms for finding silicon-wafer defects and trading from 2022 to 2026. Her current independent projects turn geographic and transport data into maps people can explore.[1]

Route estimated passengers through the scheduled network

NYC Riders combines MTA hourly origin-destination estimates with train timetables. Riders use RAPTOR routing with transfer times, and train bubbles grow with passenger counts. Departures are randomized within each reported hour. The model assumes trains run on time and does not cap passenger capacity, so the animation represents a scheduled-data simulation rather than live passenger tracking. Its reference Wednesday uses May 2026 data.[5]

Make the definition behind a language map visible

Language Dots primarily maps language spoken at home, but uses mother-tongue, native-language or estimated counts where those are the available data. People reporting multiple languages are split between them to avoid double counting. The map exposes country-specific sources and marks places without data. These distinctions matter when comparing bubbles that come from different census questions.[6]