Students for Urban Data Systems

at Carnegie Mellon University

Upcoming Projects

The upcoming projects have an expected timeline of September through mid-December, with the potential to develop into additional projects for future semesters, if there is an interest from the SUDS student team and the partner organization.

Open Positions:

  • Project Lead (Coordinate student efforts and be the point of contact with the partner organization)
  • Team Member

If you’re interested in joining any of these exciting projects, please send a copy of your resume to shouvikm@cmu.edu and mmadaio@cs.cmu.edu, and let us know the project and the position you are interested in contributing for this fall.


Remake Learning  – Understanding the Education Innovation Landscape of Pittsburgh

Remake Learning is a professional network of educators and innovators working together to shape the future of teaching and learning in the Greater Pittsburgh Region, representing more than 250 organizations, including early learning centers & schools, museums & libraries, afterschool programs & community nonprofits, colleges & universities, ed-tech startups & major employers, philanthropies & civic leaders.

For this project, they want to develop interactive maps of the organizations that make up that network, as well as the events they put on and the populations they serve through their grant offerings and educational events. We’re looking for a team of SUDS students to design and develop interactive maps to visualize their data, either for their public-facing website or for their internal planning purposes. This may likely also involve finding publicly available civic data on the City of Pittsburgh area, such as, for instance, census data, and integrating it into either the maps or a data dashboard for Remake Learning planning purposes.

Preferred Skills:

  • Involvement in this project may require skills in either data cleaning and analysis (Python, R), data visualization (R Shiny, D3.js), GIS (Mapbox, ArcGIS, etc), or web development (HTML/CSS, Javascript).
  • Experience working in education or with educational data is beneficial, but not required.

Just Harvest – Understanding Fresh Food Access in Pittsburgh

Just Harvest is a non-profit organization working to end hunger by expanding access to fresh, healthy food. The Fresh Access program helps enable shoppers to use their food stamps – as well as credit and debit cards – to buy fresh, nutritious, and locally-grown food.

For this project, they want to better understand the population they serve and the farmers’ markets currently supported through Fresh Access. To do this, they want to develop an interactive map to visualize and understand the transactions that occur at the ~300 markets they work with, to better target their support and plan for future market partnership. We’re looking for a team of SUDS students to design and develop this interactive visualization of their transaction and market data and develop a pipeline so the map can be updated as new data are collected. This may also involve finding and integrating publicly available civic data on the City of Pittsburgh area, such as, for instance, census data or SNAP data. As part of this work, they may also want additional statistical analyses to understand the pattern of market usage from their Fresh Access users.

Preferred Skills:

  • Involvement in this project may require skills in either data cleaning and analysis (Python, R), data visualization (R Shiny, D3.js), map-based visualizations (Mapbox, Leaflet, ArcGIS, etc), or web development (HTML/CSS, Javascript).
  • Experience working with customer transaction data is beneficial, but not required.

Metro21 – Improving and Extending Fire Risk Models

Metro21 is a partnership between CMU and the City of Pittsburgh and Allegheny County, to support research, development, and deployment of CMU projects that seek to solve problems in a variety of metro-related focus areas. This project is in partnership with the Pittsburgh Bureau of Fire (PBF) and the Department of Innovation and Performance.

For this project, PBF wants to understand the relative fire risk of various properties around the city, to inform their Community Risk Reduction efforts (e.g. property inspections and fire safety education events). To do this, Metro21 has already developed a machine-learning risk model trained on historical fire incident data and various features of commercial properties in the city. PBF is currently using this risk model to inform their fire inspections, but they want to improve and extend the model further with new data sources, possibly including developing a risk model for residential properties in addition to the commercial properties already included in the model.

We’re looking for a team of SUDS students to improve and extend the machine-learning risk model this semester, and to take this project in exciting new directions! This may also involve finding and integrating publicly available civic data on the City of Pittsburgh area, such as, for instance, unpaid tax liens, smoke alarm data, 311 data, and others.

Preferred Skills:

  • Involvement in this project may require skills in either data cleaning and analysis (Python, R), machine learning (Python, TensorFlow, etc), data visualization (R Shiny, D3.js), map-based visualizations (Mapbox, Leaflet, ArcGIS, etc), or web development (HTML/CSS, Javascript, Node.js, Flask, etc).
  • Prior machine learning experience strongly preferred; prior experience with models used in production contexts is even more beneficial.