Projects

FoodGrid

Civic Tech / Applied ML · 2026

Maps food access inequality across Boston census tracts with a multilingual assistant and a government simulation mode.

React · Django REST · Deck.gl · MapLibre · Llama 3.1

The FoodGrid app mapping food access inequality across Boston census tracts.

Problem

Food access is unevenly distributed across a city, but residents and policymakers lack a shared, interactive way to see and act on the gaps.

Solution

A civic app with two modes. Residents find nearby resources and chat with a multilingual assistant; government users simulate adding resources and watch the equity score change in real time across Boston census tracts.

What I Built

FoodGrid maps food access across Boston census tracts and splits into two modes for its two audiences. In resident mode, people find nearby food resources and ask questions through a multilingual LLM assistant, so the tool works for more of the city than English alone would reach. In government mode, planners simulate adding a resource to a tract and watch a live equity score update across the map, which turns a static map into something they can actually test decisions against. Both modes sit on an interactive geospatial visualization that makes the gaps legible at a glance.

Technical Details

  • React and TypeScript
  • Django REST and Node/Express
  • MongoDB Atlas
  • Deck.gl and MapLibre
  • Llama 3.1 for the multilingual assistant

What I Learned

  • A simulation mode turns a map into a decision tool for policymakers.
  • Multilingual chat made the resident side usable for more of the city.
  • Won Best Overall and Best in the EcoHack track at MLH CivicHacks.