Papers

1

Total Citations

57

H-Index

1

About

Dewu Yue is a pioneering researcher at the intersection of triboelectric nanogenerators and artificial intelligence, whose work is driving the next generation of self-powered, intelligent sensing systems. His most notable contribution is the development of triboelectric in-sensor deep learning, a paradigm-shifting approach that integrates energy harvesting, sensing, and computation directly into a single device. This innovation, detailed in his highly cited 2024 paper (57 citations), enables self-powered gesture recognition with remarkable accuracy, specifically designed for critical applications in multifunctional rescue tasks. By eliminating the need for external power sources and complex data transmission, Yue’s work addresses a fundamental challenge in deploying smart sensors in remote or hazardous environments. His research has the potential to revolutionize how first responders and autonomous systems interact with their surroundings, offering a robust, low-power solution for real-time human-machine interfaces. With his contributions rapidly gaining recognition in the field of flexible electronics and energy harvesting, Dewu Yue is establishing himself as a key innovator in creating sustainable, intelligent systems for emergency response and beyond.

Research Focus

Key Achievements

1
H-Index
1
Papers
57
Total Citations
57
Avg Citations/Paper
🏆 Most Cited Paper
Triboelectric in-sensor deep learning for self-powered gesture recognition toward multifunctional rescue tasks
57 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Shenzhen Institute of Information Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 10 days ago