Hong Xu
Software Engineer at Van Ginneke Social Enterprise
Seattle, Washington, United States
Summary
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RockstarHong Xu is a software engineer based in Seattle with 15 years of experience improving reliability and developer workflows across back-end systems, tooling, and ML models. He is a prolific open-source contributor, with practical fixes and feature work in well-known projects like GnuCash, CMake, pytest, Sphinx, and the ubiquitous oh-my-zsh. His contributions span from correcting subtle correctness bugs and documentation to adding model support and robustness in an object-detection stack, showing both attention to detail and applied ML knowledge. Hong frequently works at the intersection of developer UX and infrastructure—enhancing Emacs tooling, shell plugins, and build systems to make everyday developer tasks smoother. Colleagues would describe him as a pragmatic engineer who prefers small, high-impact changes that improve correctness and maintainability. Unexpectedly, his footprint ranges from low-level variable fixes to adding user-facing search plugins and model swaps, demonstrating breadth as well as depth.
15 years of coding experience
Stackoverflow
8,582reputation
1.2mreached
97answers
111questions
docker
top-5%
networking
top-5%
nuget
top-5%
github
top-5%
Github Skills (70)
restructuredtext10
package-management10
python10
testing10
plugin-development10
cmake10
emacs-lisp10
emacs10
sh10
computer-vision10
shell10
elisp10
cli10
debugging10
git10
Programming languages (38)
Github contributions (5)
IBM/MAX-Object-Detector
Apr 2019 - Sep 2021
Localize and identify multiple objects in a single image.
Role in this project:
ML Engineer
ML EngineerContributions:5 releases, 10 reviews, 27 commits in 2 years 5 months
Contributions summary:Hong contributed to the development and maintenance of the `ibm/max-object-detector` repository, focusing on model improvements and stability. They added support for the faster_rcnn_resnet101 model as an alternative, demonstrating an understanding of model selection. Key contributions include correcting metadata outputs for alternative models and updating the code to handle unknown image formats, enhancing the robustness of the object detector. They also updated TensorFlow to version 2.
coco-datasetdocker-imagesingle-imagemachine-learningimage-processing
editorconfig/editorconfig-emacs
Nov 2011 - Jun 2017
EditorConfig plugin for Emacs
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:30 reviews, 77 commits, 70 PRs in 5 years 7 months
Contributions summary:Hong primarily contributes to the Emacs plugin's functionality by adjusting code indentation rules and implementing support for new modes. They've added settings for various programming modes like Lisp, Ruby, HTML, and CSS, along with integrations for Web-mode, Cmake-mode, and Erlang mode. Further, they have addressed issues related to the plugin's behavior and introduced support for features like max line length and custom hooks.
elispeditorconfigemacsemacs-lspeditorconfig-plugin
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