Kay Zhu
UX Designer at Freelance
United States
Summary
👤
Senior🎓
Top SchoolKay Zhu is a seasoned UX designer with 14 years of experience crafting scalable design systems and cross-platform experiences for products at HubSpot, Meijer, and AWS. Trained in architecture and human-computer interaction at the University of Michigan, she brings a systems-thinking approach that elevates both customer-facing interfaces and internal tooling. Kay pairs hands-on visual and interaction design with coaching and governance—standardizing UX onboarding and helping teams adopt consistent component libraries. Her background in back-end development and open-source work (including performance-focused contributions to the XLA compiler and a fast Python locality-sensitive hashing library) gives her a rare fluency across design and engineering. Equally comfortable as a consultant and in-house designer, she pushes for higher UX standards while proposing pragmatic, testable ideas that scale.
14 years of coding experience
Bachelor Science of Architecture, Architecture, Bachelor Science of Architecture, Architecture at University of MichiganMaster's degree, Human Computer Interaction, Master's degree, Human Computer Interaction at University of Michigan - School of Information
English, Chinese, German
Stackoverflow
30,051reputation
3.8mreached
197answers
4questions
ftp
top-1%
django-models
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django
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html-select
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numpy
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pixel
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Github Skills (39)
simplify10
c-language10
python10
redis10
django10
ftp10
numpy10
django-models10
hashtable10
compiler10
xla10
hash10
cprogramming-language10
simplification10
web-application9
Programming languages (7)
Github contributions (5)
kayzhu/LSHash
Nov 2012 - Apr 2013
A fast Python implementation of locality sensitive hashing.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:51 commits in 5 months
Contributions summary:Kay primarily contributed to the core functionality of the LSHash library. They implemented the initial hash module, added features for indexing and querying, and refactored the codebase for performance and storage flexibility. Key contributions include the addition of different distance metrics and the refactoring of storage interfaces, which enhanced the library's functionality and scalability.
hashingpythonlocalitypython-implementationsensitive
openxla/xla
May 2017 - Mar 2019
A machine learning compiler for GPUs, CPUs, and ML accelerators
Role in this project:Back-end Developer
Back-end DeveloperContributions:77 commits in 1 year 10 months
Contributions summary:Kay made commits related to the algebraic simplification and optimization within the XLA compiler. They focused on improving the efficiency of the compiler by directly outputting empty constants in specific reshape scenarios and optimizing the movement of reshape/transpose operations. Furthermore, the user made changes to enable HloEvaluator to support additional operations like convolution, reduce, and map, as well as various data types to facilitate constant folding. These contributions enhanced the functionality and performance of the XLA compiler.
compilercommunity-drivenmachine-learningmodular
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