On July 8th, 2014, several teams for the Data Science for Social Good Program presenting their work-in-progress to a packed Chicago OpenGov Hack Night.
The fellowship, funding by the Eric & Wendy Schmidt Foundation, is a University of Chicago summer program for aspiring data scientists to work on data mining, machine learning, big data, and data science projects with social impact.
Working closely with governments and nonprofits, fellows take on real-world problems in education, health, energy, transportation, and more.
This year, the program is working with 48 fellows. This year, the partner organizations include the City of Memphis, Chicago Department of Public Health, Get Covered Illinois, Chicago Public Schools and more.
Here’s Matt Gee explaining the program in more detail.
Also presenting were two different teams, each working on a different subject area.
First up was a project to help Chicago Public Schools predict enrollment in the future. Each spring, Chicago Public Schools allocates $1.8 billion to the hundreds of public schools in its system. To determine where to distribute that money, CPS must predict next year’s enrollment for each school months ahead of time, then adjust budgets two to three weeks into the school year when the actual enrollment numbers are set. Large discrepancies between projected enrollment and the real numbers lead to large adjustments in funding, which can disrupt teachers and students. DSSG is working with CPS to develop a model that helps to predict where those changes in enrollment will occur.
The next team that presented was the team working with WikiEngery and PecanStreet Inc to build new energy residential energy management tools. Using data produced from smart meters, DSSG has a rich data set to work from. Here’s the team to explain more.
If you’d like to learn more about Data Science for Social Good, they’re holding several events over the summer that are open to the public.
