The Eric & Wendy SchmidtData Science for Social Good
Meet the 2014 Fellows and Mentors!
Last Night: Standing room only presentations at our 2014 Data Fair!
The Eric & Wendy Schmidt Data Science for Social Good fellowship 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.
For three months in Chicago they apply their coding and analytics skills, collaborate in a fast-paced atmosphere, and learn from mentors coming from industry and academia.
The 2014 program brings 48 aspiring data scientists from across the country to Chicago. They are graduate and undergraduate students from quantitative and computational fields - from computer science to machine learning to statistics to public policy.
From June 2 to the end of August, they will work in small teams on an analytics project in partnership with nonprofits, local governments, or federal agencies. Fellows will work on high impact problems, analyzing dozens of datasets, and learning from decision-makers on the front lines of public policy.
Each team is led by full-time mentors who will serve as project leads and techincal advisors.
Read our blog to follow the fellowship and learn about our projects.
The fellowship is led by Rayid Ghani from the Computation Institute & Harris School of Public Policy at the University of Chicago, and Former Chief Data Scientist of the 2012 Obama campaign. It's organized by an interdisciplinary team from the Computation Institute, a joint initiative between the University of Chicago and Argonne National Laboratory.
Director - Center for Data Science and Public Policy, Computation Institute & Harris School of Public Policy, University of Chicago. Former Chief Scientist of 2012 Obama campaign
Researcher at Computation Institute
Senior Associate Director of the Urban Center for Computation and Data, University of Chicago