Keywords: C++, Python, Prediction, Motion Planning
* Decreased driver interventions in JP by 30% by debugging the trajectory planning modules in C++ with teams in the US, e.g. triaging log data, identifying root causes on large C++ codebases, articulating solutions, and managing vehicle experiments.
* Streamlined simulation scenario generation process for the motion planning team by 3x efficiency by creating automation scripts in Python that leverage Applied Intuition API and by leading cross-functional collaboration with teams in the US.
* Enhanced safety validation for Level 4 driverless autonomous vehicles by designing and implementing a prediction evaluator in C++ with software development life cycle best practices, e.g. object-oriented design, code standards, code reviews, and testing.