Kenta Kubo
Developer at OPTiM Corporation 株式会社オプティム
Chiyoda, Japan
Summary
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Rockstar🎓
Top SchoolKenta Kubo is a developer with 12 years of experience combining mobile iOS engineering and machine learning model integration, based in Chiyoda, Japan. At OPTiM Corporation since 2017 he ships practical software solutions informed by a bachelor's in Artificial Intelligence from Kyushu Institute of Technology. His open-source work spans improving computer vision model conversions in ChainerCV and refining terminal UX for iOS/iPadOS in the well-regarded a-shell project, highlighting a knack for cross-domain problem solving. He focuses on pragmatic maintenance—fixing deprecations, polishing output, and implementing keyboard/QuickType behavior—to keep tools reliable for users and developers. An iPad power user, he brings real-world product sensibilities to developer-facing features and ML toolchains. Colleagues can expect a detail-oriented engineer who bridges research code and polished mobile experiences.
11 years of coding experience
鹿児島県立鹿屋高等学校Bachelor's degree, Artificial Intelligence, Bachelor's degree, Artificial Intelligence at Kyushu Institute of Technology
Japanese, English
Stackoverflow
59reputation
5kreached
2answers
0questions
Github Skills (16)
objective-c10
computer-vision10
wkwebview10
keyboard-input10
swift10
ios10
caffe10
mobile-development10
python10
keyboard10
machine-learning9
model-conversion9
user-interface9
deep-learning8
css6
Programming languages (23)
Github contributions (5)
holzschu/a-shell
Nov 2019 - Oct 2021
A terminal for iOS, with multiple windows
Role in this project:
Mobile Developer (iOS)
Mobile Developer (iOS)Contributions:3 reviews, 16 commits, 21 PRs in 1 year 11 months
Contributions summary:Kenta primarily contributed to the iOS terminal application by implementing and refining core features related to user interaction and terminal behavior. They fixed bugs and improved functionality by implementing keyboard shortcuts, including Unix-style control key combinations. Furthermore, the user addressed QuickType bar behavior on iOS/iPadOS 15. These changes improved the overall user experience and functionality of the terminal within the iOS environment.
multiple-windowsioswindowsterminal
chainer/chainercv
Aug 2017 - Aug 2017
ChainerCV: a Library for Deep Learning in Computer Vision
Role in this project:ML Engineer
ML EngineerContributions:7 commits, 1 PR, 5 comments in 1 day
Contributions summary:Kenta primarily worked on the `examples/ssd/caffe2npz.py` file, which suggests a focus on converting and adapting models, likely from Caffe to the ChainerCV framework. Their commits address deprecated method usages, fix output messages, and address typos. These changes indicate that the user was involved in the integration, modification, and maintenance of a computer vision model within the repository, demonstrating a hands-on approach to model adaptation and code refinement.
deep-learningpytorchcomputer-visionvision
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