Yoshi Ri
Shinagawa, Japan
Summary
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RockstarYoshi Ri is a software-focused robotics and EV control researcher with a Ph.D. in Electrical Engineering from the University of Tokyo and nine years of hands-on experience integrating image processing, control theory, and sensor fusion. He specializes in camera geometry, Kalman-filter–based information integration, and linear control of motors, with practical skills across MATLAB/Simulink, C/C++, and Python for embedded, communication, and perception systems. His industrial and academic roles at IHI Corporation and the University of Tokyo reflect a mix of product-oriented research and real-world hardware validation for FA and robotic control. As an open-source contributor to Autoware Universe, he improved perception utilities and multi-object tracking—introducing edge-case handling and enabling tracking of smaller objects—demonstrating attention to robustness and test automation. Based in Yokohama, he seeks to bring measurable, system-level improvements to products that close the loop between vision and actuation.
9 years of coding experience
Github Skills (9)
testing10
c-language10
cprogramming-language10
ros10
autonomous-driving10
kalman-filter9
3d-mapping8
missionplanner7
planning7
Programming languages (8)
Github contributions (5)
autowarefoundation/autoware_universe
Oct 2022 - Jan 2023
Role in this project:
Backend Developer & Test Automation Engineer
Backend Developer & Test Automation EngineerContributions:510 reviews, 6 commits, 206 PRs in 3 months
Contributions summary:Yoshi Ri's contributions focused on improving the `perception_utils` module by implementing and testing object classification functionalities within the `autoware_universe` repository. They added multiple unit tests for key functions like `isVehicle`, `isCarLikeVehicle`, and `isLargeVehicle`, ensuring accurate behavior across different scenarios. Furthermore, they refactored existing code, added edge case handling, and incorporated pre-commit hooks to maintain code quality. Moreover, Yoshi implemented features to enable the tracker to track smaller objects by adapting min_union_area. Yoshi also updated the multi-object tracker, implementing improvements to the bicycle model.
autowareros23d-mapcalibrationros
YoshiRi/MyMemo
Apr 2019 - Jul 2021
Contributions:68 commits, 48 pushes, 1 branch in 2 years 3 months
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