Tara Safavi
Senior Applied Scientist at Microsoft
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolTara Safavi is a Senior Applied Scientist based in Seattle with a PhD in computer science and 11 years of experience translating machine learning research into production-ready systems. At Microsoft she progressed from research internships to senior research and applied scientist roles, leading applied research efforts since 2022 and joining the senior applied scientist ranks in 2024. Her background spans knowledge graph embeddings and reproducible research—she has contributed meaningful backend fixes and feature enhancements to the LibKGE project, improving model correctness and dataset support. Tara blends deep academic training with hands-on engineering, regularly refactoring legacy code and shipping robust model infrastructure. Colleagues describe her as someone who bridges theoretical rigor and pragmatic implementation, often surfacing subtle correctness issues that improve long-term reliability.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Michigan
Stackoverflow
1reputation
0reached
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Github Skills (7)
pytorch10
graph-embedding10
knowledge-graph10
python10
machine-learning9
data-science8
data-preprocessing7
Programming languages (1)
Github contributions (5)
uma-pi1/kge
Apr 2020 - Dec 2020
LibKGE - A knowledge graph embedding library for reproducible research
Role in this project:
Back-end Developer
Back-end DeveloperContributions:12 commits, 8 PRs, 8 comments in 7 months
Contributions summary:Tara primarily focused on improving the existing codebase by fixing errors, refactoring, and adding new features. This included fixing missing return statements in the TransE scorer, updating and correcting files for the Rescal and TransE models, as well as general improvements in the KgeEmbedder class. Their contributions also involved modifying embedding initializations, and adding CoDEx datasets to the download process.
knowledgereproducibleknowledge-graphknowledge-graph-embeddinggraph
cgsavard/creative-ai
Nov 2015 - Nov 2015
Contributions:5 commits in 2 days
deep-learningcreative-aiartificial-intelligencemachine-learning
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