Kenzo Tsunekawa
Machine Learning Engineer at Woven by Toyota
Chiyoda, Japan
Summary
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Rockstar🎓
Top SchoolKenzo Tsunekawa is a machine learning engineer based in Chiyoda, Japan, with 10 years of experience building perception systems for robotics and autonomous vehicles. He blends research and production expertise—after roles at Tier IV and Sony CSL he now works at Woven by Toyota—focusing on computer vision, lidar perception and applied ML. As an active open-source contributor to Autoware.Universe, he improved lidar_centerpoint by adding a yaw normalization filter, per-class yaw thresholding and a TF-free single-frame detection mode to boost accuracy and reduce latency. His career spans academia and industry (Universidad de Chile, The University of Tokyo, mining R&D), giving him a rare combination of sensor-level understanding and field-ready engineering.
10 years of coding experience
8 years of employment as a software developer
University of TokyoBachelor of Science (B.Sc.), Licenciatura en Ciencias de la Ingeniería, Mención Eléctrica, Bachelor of Science (B.Sc.), Licenciatura en Ciencias de la Ingeniería, Mención Eléctrica at Universidad de Chile
English, Spanish, Japanese
Github Skills (10)
tensorrt10
cuda10
computer-vision10
c-language10
ros10
autonomous-driving10
c-programming-language10
machine-learning9
python8
3d-mapping7
Programming languages (6)
Github contributions (5)
autowarefoundation/autoware_universe
Sep 2022 - Dec 2022
Role in this project:
ML Engineer
ML EngineerContributions:468 reviews, 8 commits, 106 PRs in 3 months
Contributions summary:Kenzo significantly contributed to the perception stack of the Autoware.Universe project. Their work focused on enhancing the lidar_centerpoint module by implementing and integrating a yaw norm filter to improve object detection accuracy. They modified code to include per-class yaw thresholding and incorporated class remapping functionalities. Furthermore, the user updated the node to function correctly without TF dependency, providing single-frame detection capabilities.
autowareros23d-mapcalibrationros
tier4/CalibrationTools
Jul 2022 - Jan 2023
sensor calibration tools for autonomous driving and robotics
Contributions:652 reviews, 104 commits, 114 PRs in 6 months
autonomous-drivingautowarecalibrationcamera-calibrationcomputer-vision
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