Qiusen Huang

Georgia Institute of Technology

Papers

1

Total Citations

9

H-Index

1

About

Dr. Qiusen Huang is a leading researcher at the intersection of robotics, edge computing, and deep learning. His work focuses on the critical challenge of deploying computationally intensive deep neural networks (DNNs) on resource-constrained collaborative robots and edge devices. Dr. Huang’s most cited paper, “Characterizing the Execution of Deep Neural Networks on Collaborative Robots and Edge Devices” (2019, 9 citations), provides a foundational analysis of the performance bottlenecks and trade-offs involved in running DNNs on these platforms. This work is essential for enabling real-time, intelligent decision-making in autonomous systems, from manufacturing robots to smart sensors. By systematically characterizing execution patterns, Dr. Huang has helped bridge the gap between powerful AI models and the practical limitations of edge hardware. His research is highly influential for engineers and scientists developing next-generation cyber-physical systems, offering a roadmap for optimizing AI performance where it matters most—at the point of action. Dr. Huang’s contributions are paving the way for more responsive, autonomous, and intelligent robotic systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
9
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Characterizing the Execution of Deep Neural Networks on Collaborative Robots and Edge Devices
9 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Georgia Institute of Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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