Jin Mook Lee

Papers

1

Total Citations

4

H-Index

1

About

Jin Mook Lee is a leading researcher in energy-efficient deep neural network (DNN) hardware and human-robot interaction (HRI) systems. His work focuses on designing specialized processors that enable intelligent, real-time emotional interaction in mobile and embedded devices. Lee’s most cited paper, “1b-16b Variable Bit Precision DNN Processor for Emotional HRI System in Mobile Devices” (2020, 4 citations), introduces a novel look-up-table-based processing engine (LPE) and a near-zero skipper to dramatically reduce power consumption. This processor integrates a CNN-based facial emotion recognition model with an RNN-based emotional dialogue generation system, allowing robots to perceive and respond to human emotions naturally. By enabling variable bit precision from 1 to 16 bits, Lee’s architecture balances computational efficiency with accuracy, making advanced emotional AI feasible for battery-powered devices. His contributions are pivotal for the next generation of socially aware robots and mobile AI assistants, pushing the boundaries of energy-constrained intelligent systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
1b-16b Variable Bit Precision DNN Processor for Emotional HRI System in Mobile Devices
4 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 5

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago