Research, Practice, and Education at the intersection of Machine Learning and Public Policy

Our Work

We are a team of researchers at Carnegie Mellon University developing data science systems in collaboration with government and nonprofit partners to tackle real-world problems and improve societal outcomes.

We partner with government agencies, non-profits, and other organizations to collaboratively develop data science systems to improve outcomes in the areas of health, criminal justice, public safety, education, economic development, transportation, and more.

We conduct research to bridge the methodological gaps we encounter in our hands-on data science projects. We work on mitigating biases and equity issues, improving interpretability, and experimental methods for field validation of ML systems 

We conduct training programs for students, government agencies, non profits, and corporations who want to understand the utility of data science in improving societal outcomes and hands-on experience applying data science to real problems.

We develop and maintain open-source tools to help practitioners scope, develop, evaluate, and mitigate biases in data science systems. Also, we share the code from our data science projects on GitHub under an open source license.

Summer Fellowship

We plan to run the Data Science for Social Good Summer Fellowship in Summer 2026 in Pittsburgh.

The Data Science for Social Good Fellowship is a full-time summer program to train aspiring data scientists to work on data-intensive projects with social impact in a fair and equitable manner. In close collaboration with a government or nonprofit organization, fellows spend three months honing their analytical and coding skills, collaborating in a fast-paced atmosphere, and learning from full-time mentors coming from industry and academia.

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