Riichi Kudo

NTT (Japan)

Papers

4

Total Citations

18

H-Index

4

About

Riichi Kudo is a leading researcher at the forefront of integrating machine vision with wireless communications, pioneering methods to predict link quality in next-generation networks. His work addresses a critical challenge for autonomous systems—ensuring reliable connectivity for self-driving cars, robots, and remote-controlled vehicles. Kudo’s key contributions include developing vision-based object detection to forecast 5.6-GHz channel performance, a two-step prediction framework using multi-camera images, and extending these techniques to 28-GHz millimeter-wave 5G channels. His 2020 and 2022 papers on link quality prediction, each garnering 5 citations, demonstrate the early impact of his cross-disciplinary approach. In 2024, Kudo advanced the field further with a study on 5G throughput prediction using physical space information, earning 4 citations. His experimental validations with mobility robots in wireless LAN systems provide practical, real-world evidence for his theories. By fusing computer vision and radio frequency analysis, Kudo is enabling the robust, low-latency connections essential for the safe operation of autonomous machines in smart cities and industrial automation.

Research Focus

Key Achievements

4
H-Index
4
Papers
18
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Using vision-based object detection for link quality prediction in 5.6-GHz channel
5 citations · 2020
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: NTT (Japan)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago