introduction

Teawon Han studied intelligent robotics at the University of Southern California and did research in AI and robotics labs. He worked for Samsung and Hanwha in South Korea for about five years as a research engineer to develop autonomous systems for unmanned ground/aerial vehicles. Focusing on evolving reasoning(decision-making) systems to handle originally unexpected situations via experiences, like a human, he created and validated a new evolving method during his Ph.D. at Ohio State University. Also, he proposed to improve the autonomous driving system’s reasoning/decision-making ability by using the evolving method, and he obtained and ran a project with Ford successfully. After graduation, he joined Ford as a research engineer (Palo Alto, CA) and worked on reinforcement-learning-based lane change decision-making and evolving method-based behavior dynamic modeling. For the company’s needs, he has been developing sample-based / optimization-based trajectory generation (e.g., MPC). As an engineer, he always proactively proposes/develops new ideas and validates their performances not only in a simulation but also in the vehicle on the test track and public road. Because of the high competition in ADAS, he, as a Sr. Software Engineer, has been currently designing and developing new architecture/features for the next-generation Blue Cruise (Ford’s ADAS) in production.

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