Junki Ishikawa
Machine Learning Engineer, Manager at 株式会社EVERSTEEL
Tokyo, Japan
Summary
🤩
Rockstar🎓
Top SchoolJunki Ishikawa is a Machine Learning Engineer and manager based in Tokyo with a decade of experience building production ML systems and web applications. He holds a Master's in Computer Science from the University of Tsukuba and has moved between research-oriented roles and industry teams at companies like LINE, DeNA, and LY Corporation. Junki is a hands-on contributor to ChainerCV, implementing advanced computer vision models such as Xception and DeepLab variants and tooling for model conversion, highlighting practical expertise in deep learning for vision. He combines product-driven engineering with research sensibilities—comfortable turning prototypes into reliable services and supervising teams to do the same. Known for bridging server-side web work and ML model engineering, he excels at integrating models into scalable applications. His background shows a pattern of short, impactful engagements (including internships and part-time research) that accelerated both open-source and product development.
10 years of coding experience
8 years of employment as a software developer
Master's degree, Computer Science, 2, Master's degree, Computer Science, 2 at University of Tsukuba
Github Skills (8)
computer-vision10
xception10
deep-learning10
python10
chainer10
machine-learning9
tensorflow7
pytorch5
Programming languages (10)
Github contributions (5)
chainer/chainercv
Jan 2019 - Jun 2019
ChainerCV: a Library for Deep Learning in Computer Vision
Role in this project:
ML Engineer
ML EngineerContributions:50 commits, 7 PRs, 1 push in 5 months
Contributions summary:Junki primarily contributed to the implementation of deep learning models for computer vision tasks within the ChainerCV library. Their work involved defining and integrating Xception, and other DeepLab models including the implementation of SeparableASPP. The user also developed utility scripts, such as `tf2npz.py`, for converting models. Furthermore, they implemented and tested DeepLabV3plus and related components.
computer-visiondeep-learningchainerneural-networkpython
ComputerVisionLaboratory/cvlab_toolbox
Oct 2017 - Sep 2019
CVLAB's tool box
Contributions:67 commits, 4 PRs, 35 pushes in 2 years
box
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