Rayid Ghani
Distinguished Career Professor at Coleridge Initiative
Pittsburgh, Pennsylvania, United States
Summary
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Rockstar🎓
Top SchoolRayid Ghani is a Distinguished Career Professor and director-level technology leader with 13+ years applying machine learning and AI to social good and public policy across health, government, and nonprofit sectors. He co-founded the Coleridge Initiative and Data Science for Social Good, blending academic rigor with product-minded program building to move data-driven solutions into practice. Previously director of the University of Chicago’s Center for Data Science & Public Policy and chief scientist for Obama for America, he has led teams that translate research into high-impact policy applications. Technically fluent across the stack, he contributes to open-source fairness tooling like Aequitas, where he improved front-end UX and integrated back-end routes to make bias audits more accessible. Based in Pittsburgh, he pairs an MS in Machine Learning from Carnegie Mellon with entrepreneurial experience (Edgeflip) to bridge research, implementation, and real-world evaluation. Colleagues describe him as a pragmatic collaborator who prioritizes auditable, equitable systems over black-box novelty.
13 years of coding experience
8 years of employment as a software developer
B.S., Computer Science, Mathematics, B.S., Computer Science, Mathematics at The University of the SouthM.S., Machine Learning, M.S., Machine Learning at Carnegie Mellon University
Stackoverflow
1reputation
0reached
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Github Skills (8)
html10
css10
front-end-development10
ui-design10
flask9
flask-ask9
python7
javascript5
Programming languages (8)
Github contributions (5)
dssg/aequitas
Apr 2018 - Jun 2020
Bias Auditing & Fair ML Toolkit
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:28 commits, 1 PR, 22 pushes in 2 years 2 months
Contributions summary:Rayid primarily focused on front-end development, improving the user interface and overall look and feel of the Aequitas web application. Their contributions involved modifying templates (HTML) and associated styling (CSS), as well as updating the navigation and layout of the application. Additionally, they made some back-end changes, adding routes in `views.py` and modifying the web application code. The user also engaged in minor documentation updates.
machine-learningbiasmachine-biasfairness-testing
rayidghani/keystone
Nov 2016 - Jan 2022
Contributions:6 pushes, 1 branch in 5 years 2 months
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