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.
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.
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.