Papers
2
Total Citations
22
H-Index
2
About
Guanru Wang is a leading researcher in energy-efficient domain-specific architectures for autonomous micro-robotics, with a focus on vision system-on-chip (SoC) design. Her work centers on enabling fully-on-chip intelligence through the integration of non-volatile memory and hybrid processing elements. Wang’s major contributions include the development of a 22nm micro-robotic vision SoC that achieves 3.5 TOPS/W while supporting both convolutional neural networks and classic vision tasks, a critical advance for power-constrained autonomous navigation. Her flagship design, RoboVisio, demonstrates a novel hybrid processing element that efficiently handles diverse vision workloads, paired with 2MB embedded MRAM for retentive weight storage—eliminating off-chip memory dependencies. These innovations have garnered attention in the VLSI and solid-state circuits communities, with her most-cited paper accumulating 16 citations. Wang’s work directly addresses the challenge of achieving real-time, low-power intelligence in millimeter-scale robots, positioning her as a key contributor to the next generation of fully autonomous micro-robotic systems.
Research Focus
Key Achievements
Top Papers
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