Chengshu Li
Member Of Technical Staff at OpenAI
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolChengshu Li is a robotics-focused Member of Technical Staff at OpenAI with 11 years of experience spanning computer vision, reinforcement learning, and mobile manipulation research. A Stanford PhD student and former SAIL researcher, he has blended academic rigor with industry impact through internships and projects at Google DeepMind, Google Brain, and AutoX. His contributions to the widely used iGibson simulation—implementing and debugging motion planning and physics integration—reflect deep familiarity with simulation-to-control pipelines. Chengshu combines systems-level engineering (large-scale perception and data pipelines) with hands-on work in motion planners and physics engines, enabling practical advances in embodied AI. Based in Palo Alto, he brings a curious, experimentation-driven approach to building robust robotic systems that bridge simulation and real-world deployment.
11 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Stanford University
English, Chinese, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
pybullet10
robotics10
kinematics10
motion-planning10
python10
data-structure9
algorithm9
data-structures9
algorithms9
c-language4
cprogramming-language4
Programming languages (6)
Github contributions (5)
StanfordVL/iGibson
Feb 2019 - May 2022
A Simulation Environment to train Robots in Large Realistic Interactive Scenes
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 releases, 3 reviews, 1519 commits in 3 years 2 months
Contributions summary:Chengshu primarily worked on implementing and debugging motion planning functionalities within the iGibson simulation environment. This included addressing issues related to the 2D motion planner, such as correcting room boundary errors. Their work also involved the utilization of pybullet tools and the application of physics-based constraints, indicating proficiency in the physics engine integration and control within this robotics simulation project. The commits demonstrate an understanding of the internal workings of the motion planning algorithms used and the impact of code changes on the overall system's operation.
roboticssimulationrobot-simulatorrealistic3d-scenes
ChengshuLi/BIG-Bench-Hard
Jul 2023 - Jan 2024
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
Contributions:2 PRs, 144 pushes, 2 branches in 6 months
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