Houjun Liu
Undergraduate Research Associate, NLP Group
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolHoujun Liu is an NLP-focused software engineer and founder based in the San Francisco Bay Area with nine years of hands-on experience building research-grade tooling and consumer products. He currently contributes to Stanford NLP (stanza) and works in Prof. Chris Manning’s lab to mechanistically probe language models while also leading projects at CMU’s Psycholinguistics Lab and the Stanford SSI rover team. As founder of Shabang Systems and co-founder of The Condution Project, he has shipped widely used open-source and mobile task-management software and led cross-functional teams from prototyping to app-store release. His background spans applied ML for search-and-rescue drones and acoustic/semantic research for clinical speech corpora—pairing production deployments with rigorous research. Notably, he implemented tokenization postprocessing and coreference refactors in the popular stanza library, reflecting a blend of production engineering and linguistic insight.
9 years of coding experience
5 years of employment as a software developer
The Nueva SchoolParticipant, Participant at LaunchX Entrepreneurship ProgramUniversity of California Santa CruzBachelor of Science - BS Computer Science — AI, Bachelor of Science - BS Computer Science — AI at Stanford University
English, Chinese, Spanish
Stackoverflow
286reputation
35kreached
1answer
3questions
Github Skills (13)
tokenize10
pytorch10
tokenizer10
nlp10
python10
natural-language-processing10
machine-learning9
deep-learning8
artificial-intelligence8
deeplearning-ai8
webassembly6
wpf6
geometry6
Programming languages (15)
Github contributions (5)
stanfordnlp/stanza
Oct 2023 - Apr 2025
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
Role in this project:
Back-end Developer
Back-end DeveloperContributions:90 reviews, 25 PRs, 241 pushes in 1 year 6 months
Contributions summary:Houjun implemented a tokenization postprocessor, enhancing the existing tokenization process in the Stanford NLP Python library. Their work involved modifying the `stanza/models/tokenization/utils.py` file to include the postprocessor, allowing for manual token cleanup and customization. They also added tests to verify the postprocessor and reassembly functions. Further contributions include refactoring of existing coreference codebase to deal with the data augmentations
nlppytorchhuman-languagesnamed-entity-recognitionpython
Jemoka/.emacs.d
Aug 2021 - Dec 2022
Contributions:101 commits, 132 pushes, 1 branch in 1 year 4 months
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