Junya Ishihara
Associate Professor
Chiyoda, Japan
Summary
🤩
Rockstar🎓
Top SchoolJunya Ishihara is an associate professor and serial founder with 17 years of software engineering and product leadership experience, currently leading web-service ventures as CEO of Machiquest and Tsukurusha while teaching at Aoyama Gakuin University. He blends hands-on Ruby on Rails development and full-stack contributions—ranging from accessible mobile maps to machine-learning-enabled web components—with deep expertise in internationalization and localization. His background includes four years at a San Francisco software company and long-standing roles in I18N/L10N QA and technical support at Genesys, giving him rare product-and-globalization fluency. An active open-source contributor, he has improved ml5.js front-end ML features and enhanced a community AED mapping project for mobile responsiveness and UX. Junya aims to create web services that serve users of all ages and nationalities and is open to roles in the USA or Canada. He often combines academic rigor with practical, award-winning prototypes—several of which (voice-recognition quizzes and location-aware social tools) have won industry recognition.
17 years of coding experience
12 years of employment as a software developer
University of Tokyo
Stackoverflow
35reputation
3kreached
0answers
2questions
Github Skills (15)
html10
css10
machine-learning10
responsive-design10
javascript10
p5js10
optimization9
optimisation9
neural-network9
deep-learning8
deeplearning-ai8
api-design7
openstreetmap7
windows6
windows-runtime6
Programming languages (15)
Github contributions (5)
CodeForChofu/AEDmap
Dec 2022 - Dec 2022
AEDマップ © Chofu Mapping Party Contributors, CC BY 4.0
Role in this project:
Front-end Developer
Front-end DeveloperContributions:14 commits, 1 PR, 18 pushes in 4 days
Contributions summary:Junya primarily focused on enhancing the user interface and user experience of an AED map application. Their contributions include making the map responsive for mobile devices, adding a title, implementing a user location tracking feature, and integrating a feedback form via Google Forms. The user also improved the presentation of AED data by adding marker color-coding based on update timestamps and providing a display of the updated date.
adobe-experience-managerpartymahjongcc-byeagle
ml5js/ml5-library
Feb 2019 - Jan 2021
Friendly machine learning for the web! 🤖
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:6 commits, 6 PRs, 10 comments in 1 year 10 months
Contributions summary:Junya primarily worked on the ml5.js library's front-end components and machine-learning integration. Their contributions included adding the library version to the build process and refactoring the KNNClassifier to enable users to load datasets from raw data. Further contributions are evident in the fix for single pose mode implementation. These changes indicate a focus on enhancing the library's functionality and user experience.
machine-learninglstmdeep-learningimagenetjavascript
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