Chang Hyeon Kim
Papers
1
Total Citations
4
H-Index
1
About
Chang Hyeon Kim is a leading researcher in energy-efficient deep neural network (DNN) hardware and human-robot interaction (HRI) systems, with a focus on enabling intelligent, emotionally-aware mobile devices. His most cited work introduces a groundbreaking variable bit precision DNN processor that operates from 1b to 16b, featuring a novel look-up-table-based processing engine (LPE) and a near-zero skipper for dramatic energy savings. This processor powers a complete emotional HRI system, integrating a CNN-based facial emotion recognition model with an RNN-based emotional dialogue generation model, allowing mobile devices to perceive and respond to human emotions in real time. Although early in its citation impact (4 citations), this work represents a significant step toward deploying sophisticated AI interaction capabilities on resource-constrained platforms. Kim’s contributions bridge the gap between hardware efficiency and affective computing, paving the way for more natural, responsive, and emotionally intelligent robotic companions and mobile assistants.
Research Focus
Key Achievements
Top Papers
- 1