Yuta Okamoto
Engineer at Preferred Networks, Inc.
Tokyo, Japan
Summary
🤩
Rockstar🎓
Top SchoolYuta Okamoto is a Tokyo-based engineer with 14 years of experience building scalable backend systems and contributor-facing features at both enterprise and open-source projects. He has worked on large-scale distributed data processing at Canon and now develops cutting-edge solutions at Preferred Networks, combining practical engineering with research-oriented toolchains. His open-source work spans deep learning and scientific computing libraries (Chainer, CuPy) as well as web and admin tooling, where he’s added type hints, GPU-aware array handling, and SQLAlchemy/FastAPI admin improvements. He also contributes front-end localization and accessibility touches—such as Japanese headers/footers—to widely referenced guides like Twitter’s Effective Scala. Colleagues describe him as detail-oriented and safety-minded, evidenced by atomic transaction fixes in django-axes and careful flake8/autopep8 cleanups. Trained in Information and Network Engineering at Waseda University, he blends systems-level rigor with practical improvements that make developer tools more reliable and usable.
14 years of coding experience
9 years of employment as a software developer
ME, Information and Network Engineering, ME, Information and Network Engineering at Waseda University
English
Stackoverflow
321reputation
35kreached
9answers
7questions
Github Skills (47)
fastapi10
admin10
python10
django10
chainer10
css10
gpu-programming10
user-authentication10
authentication10
forms10
numpy10
typehinting10
maintainability10
sqlalchemy10
starlette10
Programming languages (16)
Github contributions (5)
twitter/effectivescala
Feb 2012 - Feb 2014
Twitter's Effective Scala Guide
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:130 commits in 2 years
Contributions summary:Yuta primarily contributed to the front-end aspects of the project, focusing on HTML and CSS modifications. They updated the character set, and added and merged code for Japanese versions of the header and footer files. There are also instances of merging from upstream repositories and publishing configurations.
effectivescalatwitter
chainer/chainer
Nov 2018 - Oct 2019
A flexible framework of neural networks for deep learning
Role in this project:Back-end Developer
Back-end DeveloperContributions:127 commits, 39 PRs, 13 pushes in 10 months
Contributions summary:Yuta primarily contributed to the project by adding type hints to various classes within the `chainer/chainer` repository, specifically focusing on the `chainer/link.py` file. These commits demonstrate a focus on improving code readability and maintainability by incorporating type annotations. The user also fixed flake8 and autopep8 warnings.
cudapythonmxnetcaffe2flexible-framework
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