Jihui Lee

Korea Advanced Institute of Science and Technology

Papers

Total Citations

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About

Jihui Lee is an emerging researcher in artificial intelligence and robotics, with a primary focus on sensor fusion for autonomous systems and reinforcement learning for robotic control. Her work addresses two critical challenges in modern AI: enabling robust perception through multi-modal data integration and developing efficient learning strategies for complex motor tasks. In her highly cited 2023 paper on "Sensor Fusion by Spatial Encoding for Autonomous Driving," Lee introduced a novel method combining Transformer architectures with Convolutional Neural Networks to fuse camera and LiDAR data, achieving enhanced perception accuracy for autonomous vehicles—a contribution that has already garnered significant attention in the field. Her complementary research on "Kick-motion Training with DQN in AI Soccer Environment" demonstrates innovative applications of reinforcement learning to overcome the curse of dimensionality in robotic motion planning, training agents to perform precise kicking actions through deep Q-networks. While early in her career, Lee's work bridges theoretical advances in spatial encoding and practical implementations in autonomous driving and robotics, establishing her as a promising voice in sensor fusion and AI-driven control systems.