Yakun Sophia Shao

University of California, Berkeley

Papers

2

Total Citations

16

H-Index

1

About

Yakun Sophia Shao is a leading researcher in computer architecture, with a focus on hardware-software co-design for emerging domains like robotics and machine learning. Her work bridges the gap between application demands and efficient silicon implementation, particularly through full-stack evaluation frameworks and specialized heterogeneous systems-on-chip (SoCs). Shao’s notable contributions include the development of RoSÉ, a pre-silicon co-simulation infrastructure that enables comprehensive, full-stack evaluation of robotics SoCs—from algorithms to hardware—addressing critical challenges in autonomous systems like UAVs and self-driving cars. She also led the design of MAVERIC, a 16nm heterogeneous SoC integrating 4 cores and 13 INT8/FP32 accelerators, achieving 72 FPS and 10 mJ/frame for ML and robotics workloads such as 3D reconstruction. This work demonstrates her impact on energy-efficient, real-time processing. With her papers garnering citations that reflect growing interest in domain-specific architectures, Shao’s research is shaping the future of agile, high-performance computing for autonomous and intelligent systems. Her achievements underscore a commitment to enabling practical, scalable solutions at the intersection of hardware and software.

Research Focus

Key Achievements

1
H-Index
2
Papers
16
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
RoSÉ: A Hardware-Software Co-Simulation Infrastructure Enabling Pre-Silicon Full-Stack Robotics SoC Evaluation
15 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: University of California, Berkeley

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago