Crystal Qian
Senior Research Scientist at Google AI
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolCrystal Qian is a senior research scientist and software engineer with 11 years of experience building scalable ML and data infrastructure at Google, DeepMind, and Google AI. She bridges research and production, contributing to core workflow tooling like Apache Airflow (improving GCP Dataproc integrations) and interactive ML interpretability front-ends such as the LIT embeddings projector. Her background spans backend systems, data pipelines, and UI polish—evidenced by contributions to ASP.NET tooling and GCP training DAGs—so she comfortably navigates both low-level code generation and cloud-native pipelines. Based in New York with degrees from Princeton and MIT, she combines rigorous CS foundations with economics-and-policy insight, enabling technical work that considers broader product and societal context.
11 years of coding experience
6 years of employment as a software developer
Master's Economics and Policy, Master's Economics and Policy at Massachusetts Institute of TechnologyAdvanced Placement/Early Action Pre-College, Advanced Placement/Early Action Pre-College at Carnegie Mellon UniversityBachelor of Science and Engineering (B.S.E.) Computer Science, Bachelor of Science and Engineering (B.S.E.) Computer Science at Princeton University
Stackoverflow
101reputation
70kreached
4answers
0questions
Github Skills (53)
asp-net-core-mvc10
unit-testing10
razor10
apache-airflow10
google-cloud-platform10
javascript10
bigquery10
data-pipelines10
python10
data-engineering10
testing10
net10
storage10
work-flow10
typescript10
Programming languages (8)
Github contributions (5)
PAIR-code/lit
May 2022 - Jan 2023
The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.
Role in this project:
Front-end Developer
Front-end DeveloperContributions:64 commits in 8 months
Contributions summary:Crystal primarily contributed to the front-end of the LIT project, focusing on the "Embeddings Projector" and the "Metrics Module." They integrated module toolbars and footers, implemented a loading spinner to improve the user experience, and added a feature to reset the view within the embeddings module. Moreover, they worked on the user interface and refactoring the backend, which involved adding color legends and implementing a global search box within the data table.
ml-modelspythoninterpretabilitydata-sciencedeep-learning
aspnet/Mvc
Jun 2016 - Sep 2016
[Archived] ASP.NET Core MVC is a model view controller framework for building dynamic web sites with clean separation of concerns, including the merged MVC, Web API, and Web Pages w/ Razor. Project moved to https://github.com/aspnet/AspNetCore
Role in this project:Back-end Developer
Back-end DeveloperContributions:7 commits, 8 PRs, 12 pushes in 2 months
Contributions summary:Crystal primarily focused on resolving issues and improving the functionality of the ASP.NET Core MVC framework. Their contributions involved correcting parameter orders and ensuring proper attribute handling within the `StringLengthAttributeAdapter`. Additionally, they addressed and resolved inconsistencies in various view result variants, specifically focusing on model properties in ViewResult, PartialViewResult, and ViewComponentResult. Furthermore, the user added View Component Tag Helper code generators.
razorcontrollermvc-coreweb-mvcseparation
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