Papers

2

Total Citations

22

H-Index

2

About

Hyochan An is a leading innovator in energy-efficient, domain-specific system-on-chip (SoC) design for autonomous micro-robotics and embedded vision. His research centers on enabling fully-on-chip intelligence for resource-constrained platforms, with key contributions in hybrid processing architectures and emerging memory integration. An’s most cited work introduces a flexible micro-robotic vision SoC fabricated in 22nm technology, achieving an impressive 3.5 TOPS/W efficiency. This design features a novel hybrid processing element (PE) that efficiently handles both convolutional neural network (CNN) and non-CNN vision tasks, paired with 2MB of embedded MRAM (eMRAM) for retentive, fully-on-chip weight storage—eliminating off-chip memory dependencies. His follow-up work, RoboVisio, extends this architecture specifically for autonomous navigation, demonstrating how domain-specific SoCs can deliver high efficiency and flexibility for real-time micro-robot vision. With over 20 combined citations for these foundational papers, An’s contributions are shaping the future of intelligent, low-power edge devices. His achievements represent a critical step toward practical, self-contained micro-robots capable of complex visual processing without cloud or external memory support.

Research Focus

Key Achievements

2
H-Index
2
Papers
22
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
A 22nm 3.5TOPS/W Flexible Micro-Robotic Vision SoC with 2MB eMRAM for Fully-on-Chip Intelligence
16 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of Michigan–Ann Arbor, Apple (United States)

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago