Ruiqi Ye

University of Manchester

Papers

1

Total Citations

3

H-Index

1

About

Ruiqi Ye is a researcher at the forefront of embedded computer vision and efficient robotics perception. Their work centers on accelerating Visual Odometry (VO) systems—critical for enabling autonomous navigation in drones and immersive experiences in AR/VR headsets—by bridging the gap between algorithm design and hardware implementation. In their highly cited 2023 paper, "Exploring Sparse Visual Odometry Acceleration With High-Level Synthesis," Ye demonstrates how modern high-level synthesis tools can optimize VO pipelines for resource-constrained platforms, achieving significant performance gains without sacrificing accuracy. This contribution, already garnering 3 citations, addresses a pressing challenge in deploying real-time spatial awareness on low-power devices. By systematically analyzing the trade-offs between speed, energy efficiency, and precision, Ye provides a practical roadmap for engineers and researchers seeking to bring robust VO to edge systems. Their work not only advances the state of the art in hardware-software co-design but also lays the foundation for next-generation autonomous systems that must see and move intelligently within tight power budgets.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Exploring Sparse Visual Odometry Acceleration With High-Level Synthesis
3 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Manchester

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago