Chao Qu is a Staff Software Engineer specializing in pose estimation and autonomy, currently driving Pose, Autonomy work at Rivian after earlier autonomy roles at Skydio and a PhD in CIS from the University of Pennsylvania. He combines academic rigor—published research in visual and lidar odometry and a dissertation on fusing visual odometry with deep-learning depth completion—with three years of industry autonomy experience building production perception stacks. A pragmatic C++ and back-end contributor to notable open-source robotics tooling like Symforce, he focuses on performance, modernizing code, and robust code generation for nonlinear optimization. Based in California, he brings a rare mix of research depth and hands-on systems engineering in vehicle and drone autonomy, with roots in automotive engineering and precision agriculture applications.
3 years of coding experience
3 years of employment as a software developer
Bachelor Automotive Engineering, Bachelor Automotive Engineering at Tongji University
Doctor of Philosophy (PhD) CIS, Doctor of Philosophy (PhD) CIS at University of Pennsylvania
Fast symbolic computation, code generation, and nonlinear optimization for robotics
Role in this project:
Back-end Developer
Contributions:22 reviews, 12 commits, 5 PRs in 1 month
Contributions summary:Chao primarily contributed to the Symforce project by optimizing code and refactoring existing functionality. Their work involved improving performance by reducing functor copies in factor creation and using more efficient C++ features. They also addressed build and linting issues by updating code to use more modern C++ standards. Additionally, the user modified the code generation to resolve issues related to the "compose_with_point" function.
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Chao Qu - Staff Software Engineer, Pose, Autonomy at Rivian