Julia Neagu is an AI research leader and founder with 8 years of experience building data-driven products and teams at the intersection of large language models and developer tools. Based in Boston, she co-founded Quotient AI (acquired by Databricks) and now leads AI Research at Databricks after driving Copilot’s data strategy and evaluation as Director of Data Science at GitHub. Her background blends a Harvard Ph.D. in Physics with practical ML/analytics execution—ranging from architecting CI/CD libraries for ML pipelines and product experimentation frameworks to launching high-impact features like the GitHub Feed. She’s skilled at translating rigorous research into production metrics, telemetry, and evaluation systems that improve model quality and user outcomes. Not obvious from titles: she has a history of cross-domain problem solving from viral dynamics modeling and stochastic optimization to IP-focused machine learning products, which informs her pragmatic approach to AI safety and evaluation.
8 years of coding experience
15 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Physics, Doctor of Philosophy (Ph.D.), Physics at Harvard University
Bachelor of Arts (B.A.), Physics. Minors: Biophysics, Finance, Applied &Computational Mathematics, Applications of Computing., Bachelor of Arts (B.A.), Physics. Minors: Biophysics, Finance, Applied &Computational Mathematics, Applications of Computing. at Princeton University
The open source version of the AWS Data Pipeline documentation. To provide feedback & requests for changes, submit issues in this repository, or make proposed changes & submit a pull request.
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Code examples used in the official AWS SDK documentation.
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