Highly experienced AI & Autonomous Driving Engineer specializing in Lon-decision and trajectory-making algorithms for autonomous driving especially for mapless. Expertise in planning, control, and optimization techniques such as MPC/LQR/QP, POMDP, Monte Carlo Tree Search (MCTS), Reinforcement Learning (RL), and AI-based search methods. Strong background in multi-threaded C++ development, numerical optimization, and embedded systems. Passionate about developing robust and efficient decision-making algorithms to advance L2++ autonomy.
•Design and implement decision planning algorithms on mapless for lon decision and lon trajectory calculation, aimed to have a algothrim-based method to solve lon problems, especially for merging\intersection\open space environment.
•Collaborate closely with cross-functional teams to seamlessly integrate decision planning and trajectory algorithms into the overall autonomous driving system architecture.
•Analyze and address real-world challenges related to L2++ autonomy, including noisy input, unstable prediction, multiple predictions, with best result for the current frame and a stable/robust interactive decision.
•Continuously optimize and enhance gaming algorithms\optimization lon trajectory to improve overall system efficiency, adaptability, and reliability.
•Participate in project planning, milestone setting, and progress tracking to ensure timely delivery of autonomous driving features for mass production.
•Ability and self-awareness to read and reproduce papers to solve complex problems.
