Huiming Zhou
Tech Lead Manager at Horizon Robotics
Pudong, Shanghai, China
Summary
🤩
Rockstar🎓
Top School
Top expert inAutonomous Robotics and Simulation Technology
Huiming Zhou is a Tech Lead Manager with six years' experience specializing in behavior decision and motion planning for autonomous driving. Based in Pudong, Shanghai, he leads multiple R&D teams at Horizon Robotics, owning the data closed-loop pipeline and end-to-end single-stage driving model performance that supported mass-production OTA releases of Horizon SuperDrive. His background spans hands-on algorithm work—game-theoretic lane-change and merging strategies, hybrid A*/RRT/Reeds-Shepp implementations—and practical productization from simulation-based testing to post-training optimization. Previously at Huawei he helped scale urban decision systems for ADS2.0/3.0, and his open-source repos demonstrate a sustained focus on path planning and visualization tools used for research and prototyping. He combines academic training from UC San Diego and BIT with a racecar team leadership win in Asia, reflecting both rigorous engineering and applied systems instincts. Colleagues can expect a leader who bridges algorithmic depth with production delivery and an appetite for building reusable planning libraries.
6 years of coding experience
4 years of employment as a software developer
University of California, San DiegoBachelor of Science Vehicle Engineering, Bachelor of Science Vehicle Engineering at Beijing Institute of Technology
Chinese, English
Github Skills (11)
algorithm10
data-structures10
algorithms10
pathfinding10
motion-planning10
python10
data-structure10
visualizations9
matplotlib9
visualization9
autonomous-vehicles9
Programming languages (1)
Github contributions (5)
zhm-real/PathPlanning
Jun 2020 - Dec 2020
Common used path planning algorithms with animations.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:288 commits, 1 PR, 236 pushes in 6 months
Contributions summary:Huiming contributed significantly to the development of path planning algorithms, implementing various algorithms like Breadth-First Search (BFS), Dijkstra's Algorithm, and A* search. Their contributions included modifying and integrating these algorithms within the provided framework. They also demonstrated their expertise in visualizing the results of these algorithms.
path-planninganimationplanning-algorithmsplanninganimations
zhm-real/MotionPlanning
Jul 2020 - Nov 2020
Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:115 commits, 1 PR, 75 pushes in 4 months
Contributions summary:Huiming appears to be working on motion planning algorithms for autonomous vehicles, specifically focusing on path planning and path tracking. The commits reveal modifications to Python files related to Rapidly-exploring Random Trees (RRT) path planning, Reeds-Shepp path generation, and Hybrid A* search. They contribute by integrating motion planning algorithms with utility libraries and environment setup in Python.
pybulletmodel-predictive-controlplanningpure-pursuitrobotics
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