Ji Feng is a Robotics Systems Engineer based in San Francisco with a year of industry experience building simulation, firmware, and embedded systems for robotics and automotive applications. Currently at NVIDIA, Ji develops robotic simulations on Omniverse/Isaac and previously contributed sensor and quadruped simulations as well as body-control firmware for Tesla’s vehicles and Semi truck. He brings a mechatronics background from the University of Waterloo and hands-on expertise in ROS, C++, Python, embedded C, and ML-enabled vision pipelines that powered an award-winning display testing tool at ecobee. Ji has practical autonomy experience from WATonomous and research work in human-robot interaction, plus a track record of shipping factory-scale tooling and automated test infrastructure. Notably, he blends low-level firmware work with high-fidelity simulation—making him comfortable moving a capability from hardware prototype to virtual testing and production scale.
1 year of coding experience
4 years of employment as a software developer
Certificate Program, Certificate Program at International Baccalaureate
Bachelor of Applied Science - BASc, Mechatronics Engineering and Artificial Intelligence Option with distinction, 85+, Bachelor of Applied Science - BASc, Mechatronics Engineering and Artificial Intelligence Option with distinction, 85+ at University of Waterloo
Unified framework for robot learning built on NVIDIA Isaac Sim
Contributions:4 pushes, 1 branch in 2 days
roboticsnvidiagpusimreinforcement-learning
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