Hong W
Staff Software Engineer at The Apache Software Foundation
Sunnyvale, California, United States
Summary
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Rockstar🎓
Top SchoolHong W is a Staff Software Engineer with 13 years of experience specializing in ML infrastructure, databases and storage systems, now based in Sunnyvale and currently at Meta. He has led database performance and autonomous tuning research at Alibaba DAMO Academy with multiple SIGMOD/VLDB publications, and helped productionize ML workflows and engines earlier at Petuum. As an Apache HAWQ PMC member and long-time committer, he brings deep distributed SQL and storage expertise, and his open-source work includes back-end improvements to DyNet and refactoring of libyarn for Apache HAWQ. Hong combines rigorous research-driven solutions with hands-on kernel and systems engineering, and has a track record of turning advanced ML and DB research into robust, testable production code.
13 years of coding experience
12 years of employment as a software developer
Computer Science, Computer Science at Tsinghua University
Stackoverflow
2,868reputation
307kreached
6answers
86questions
Github Skills (19)
unit-testing10
develop10
c-language10
computer-engineering10
cprogramming-language10
serialization9
machine-learning9
data-serialization9
cmake8
build-system8
boost-asio6
version-control6
boost6
amazon-ec26
buffer6
Programming languages (5)
Github contributions (5)
apache/hawq
Mar 2016 - Jan 2017
Apache HAWQ
Role in this project:
Back-end Developer
Back-end DeveloperContributions:105 commits, 139 PRs, 492 comments in 9 months
Contributions summary:Hong primarily focused on refactoring and upgrading the `libyarn` library within the `apache/hawq` repository. Their work included fixing bugs related to higher versions of GCC, upgrading `libyarn`'s version number, and adjusting code related to failover handling. The changes were applied across multiple source files, indicating a focused effort to improve the library's stability and compatibility. The user also made adjustments to support the inclusion of `libhdfs3` and GoogleTest/Gmock.
hawqolapsqlapachedatastream
clab/dynet
Feb 2017 - Apr 2018
DyNet: The Dynamic Neural Network Toolkit
Role in this project:Back-end Developer
Back-end DeveloperContributions:127 commits, 96 PRs, 53 pushes in 1 year 2 months
Contributions summary:Hong primarily contributed to bug fixes and code improvements within the DyNet library. Their work involved addressing incorrect assignments and typos in various C++ files, specifically focusing on the TreeLSTM and examples related to Poisson regression, and RNNLM models. They also turned on and refined unit tests, along with the implementation of serialization features, including macro interfaces for serialization and definition, to ensure the software's robustness and data integrity.
dynetdynamic-neural-networkdeep-learningneural-networksmachine-learning
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