Bumgeun Park

Korea Advanced Institute of Science and Technology

Papers

Total Citations

H-Index

About

Bumgeun Park is an emerging researcher at the intersection of robotics, autonomous systems, and artificial intelligence, with a primary focus on reinforcement learning (RL) and sensor fusion. His work addresses critical challenges in real-world automation, from household efficiency to autonomous driving. Park’s most cited paper, “Path Planning of Cleaning Robot with Reinforcement Learning” (2022, 15 citations), tackles the pressing issue of energy consumption in household robots by developing efficient, RL-driven navigation strategies. This work highlights his ability to apply advanced AI to practical, everyday problems. In “Sensor Fusion by Spatial Encoding for Autonomous Driving” (2023, 4 citations), Park explores the fusion of camera and CNN-Transformer data to enhance perception systems—a vital contribution to safe autonomous navigation. His third paper, “Kick-motion Training with DQN in AI Soccer Environment” (2023, 2 citations), demonstrates his skill in overcoming the curse of dimensionality in RL, training agents to perform complex, precise motions in simulated environments. Though early in his career, Park’s research shows a clear trajectory toward integrating learning-based methods with physical systems, promising impactful advances in robotics and autonomous driving.