Summary
Kyuhwan Yeon is a robotics researcher and engineer with nine years of experience building scalable, interpretable robot learning and autonomous driving systems. Currently a DPhil student at Oxford’s Mobile Robotics Group, he blends academic rigor with hands-on deployment experience from roles at 42dot where he developed map-free motion prediction, learning-based motion planning, and real-time C++ inference pipelines for Level 4 urban autonomy. His background spans control and estimation (MPC, EKF), neural approaches to engine and vehicle modeling, and continuous learning pipelines that bridge simulation and road testing. Based in Oxford and with a practical interest in Physical AI, he brings a rare combination of production-grade systems engineering and research-driven algorithm design.
8 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Engineering Science, Doctor of Philosophy - PhD, Engineering Science at University of Oxford
Master of Science - MS, Automotive Electronics and Control Engineering, Master of Science - MS, Automotive Electronics and Control Engineering at Hanyang University
Self driving cars, C++, ROS, Self driving cars, C++, ROS at Udacity
Bachelor's degree, Automotive Engineering, Bachelor's degree, Automotive Engineering at 한양대학교
English, Korean