Gyeong-Su Kim
Papers
1
Total Citations
11
H-Index
1
About
Gyeong-Su Kim is a researcher whose work sits at the intersection of robotics and acoustic signal processing, with a primary focus on enabling robots to hear clearly in noisy, real-world environments. His key research areas include sound source localization (SSL), noise suppression, and microphone array processing for mobile platforms. Kim’s most cited work, “MIMO Noise Suppression Preserving Spatial Cues for Sound Source Localization in Mobile Robot” (2021, 11 citations), addresses a critical challenge in robotics: the interference of ego-noise—such as motor hum—with a robot’s ability to locate sounds. He proposed a multi-input multi-output (MIMO) noise suppression algorithm that effectively filters out dominant self-generated noise while preserving essential spatial cues, allowing for accurate SSL even in dynamic, noisy conditions. This contribution is particularly valuable for applications in human-robot interaction, search-and-rescue, and autonomous navigation, where auditory awareness is key. Though early in his citation impact, Kim’s work demonstrates a thoughtful integration of signal processing theory with practical robotic constraints, marking him as a promising voice in the field of robot audition.
Research Focus
Key Achievements
Top Papers
- 1