Qi Luo
Distinguished Engineer And Director Of Engineering at NVIDIA
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolQi Luo is a Distinguished Engineer and Director of Engineering with a Ph.D. in Mechanical Engineering and 12+ years building autonomous driving, robotics, and embedded control systems for industry leaders like NVIDIA and Baidu. He led the design and shipping of vision-based city NOA products and was a principal architect for Baidu’s Apollo open-source autonomous driving platform, contributing key MPC and lateral control work visible on GitHub. His expertise spans model-based control, trajectory optimization, sensor fusion, and inference-optimized ML pipelines, with hands-on experience across C/C++, MATLAB/Simulink, RTOS and production ECUs. Qi blends deep algorithmic research (MPC, IMM/Kalman filtering, statistical data association) with product-grade system integration, having won a national patent award and shipped L2+ systems to OEMs. Based in the San Francisco Bay Area, he mentors engineering teams while still making technical commits to open-source autonomy projects—a balance of leadership and low-level craftsmanship.
12 years of coding experience
12 years of employment as a software developer
Ph.D Mechanical Engineering, Ph.D Mechanical Engineering at Purdue UniversityBachelor Mechanical Engineering, Bachelor Mechanical Engineering at Shanghai Jiao Tong University
Github Skills (8)
control-systems10
c-language10
cprogramming-language10
autonomous-driving10
algorithm9
algorithms9
object-tracking8
sensor-fusion8
Programming languages (5)
Github contributions (5)
ApolloAuto/apollo
Jul 2017 - Nov 2020
An open autonomous driving platform
Role in this project:
Backend Developer
Backend DeveloperContributions:33 reviews, 1730 commits, 1212 PRs in 3 years 4 months
Contributions summary:Qi made several commits focused on modifying and extending the lateral controller, including adding reference papers and updating MPC solver and test files. They also worked on incorporating pitch angle compensation and gear shift logic. In addition, the user was involved in refactoring the canbus protocol and adding features for improved autonomy, such as adding code for audio event and the associated proto files and enabling testing with simulated localization in the control side.
autonomousmachine-learningautonomyautonomous-drivingapollo
Capri2014/apollo
Dec 2017 - Nov 2020
An open autonomous driving platform
Contributions:140 commits, 1 PR, 737 pushes in 2 years 11 months
autonomousmachine-learningautonomous-drivingautopilotmavlink
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