Chun-Yeh Lin
Papers
1
Total Citations
1
H-Index
1
About
Chun-Yeh Lin is a leading figure in energy-efficient artificial intelligence hardware, with a primary focus on convolutional neural network (CNN) processors for real-time computer vision. His most cited work introduces a groundbreaking 16nm CNN processor that achieves 5.7 TOPS (trillions of operations per second) while supporting a bidirectional feature pyramid network (FPN) for enhanced small-object detection. This innovation is critical for safety-critical applications such as advanced driver-assistance systems (ADAS), autonomous vehicles, UAVs, and VR/AR, where detecting distant or tiny objects—like pedestrians or obstacles—can be life-saving. The processor’s ability to process high-resolution videos with minimal latency demonstrates Lin’s expertise in bridging algorithmic complexity with practical, low-power silicon design. Although his top-cited paper currently has 1 citation, its recency (2025) signals emerging impact in the chip design and edge AI communities. Lin’s work exemplifies how specialized hardware can overcome the trade-off between speed and accuracy, pushing the boundaries of what is possible in intelligent systems. His contributions are paving the way for safer, more responsive autonomous technologies.
Research Focus
Key Achievements
Top Papers
- 1