Hun-Seok Kim
Papers
2
Total Citations
22
H-Index
2
About
Hun-Seok Kim is a leading figure in energy-efficient, domain-specific system-on-chip (SoC) design for autonomous micro-robotics and embedded vision. His research centers on creating highly flexible, intelligent hardware that can perform complex vision tasks—including both convolutional neural networks (CNNs) and classic computer vision algorithms—entirely on-chip, without relying on external memory or cloud processing. Kim’s major contributions include pioneering the use of embedded MRAM (eMRAM) for retentive, fully-on-chip weight storage, dramatically reducing power consumption and latency in autonomous navigation systems. His flagship work, the RoboVisio SoC, demonstrates a novel hybrid processing element that achieves exceptional efficiency for both CNN and non-CNN workloads. Fabricated in advanced 22nm technology, his designs have achieved remarkable energy efficiencies of up to 3.5 TOPS/W, with key papers accumulating over 20 citations. By enabling fully-on-chip intelligence for micro-robots, Kim’s work is paving the way for next-generation autonomous systems that are smaller, faster, and more power-efficient than ever before.
Research Focus
Key Achievements
Top Papers
- 1
- 2