Papers

8

Total Citations

145

H-Index

6

About

Qiuquan Guo is a pioneering researcher at the intersection of intelligent robotics, flexible electronics, and advanced manufacturing. His work centers on developing next-generation sensing and actuation systems that bridge the gap between soft materials and autonomous machines. Guo’s major contributions include the creation of flexible large-area e-skin arrays using patterned laser-induced graphene for tactile perception (38 citations), and multilayer graphene/PDMS composite gradient materials for high-efficiency photoresponse actuators (25 citations). He has also advanced wireless pressure sensing through radio frequency resonator-based designs with MWCNT-PDMS bilayer microstructures (16 citations). In robotics, Guo developed an inverse kinematics solution for 6-degree-of-freedom manipulators using deep reinforcement learning (39 citations), demonstrating how AI can enhance industrial automation. His work on initiator-integrated 3-D printing of magnetic objects for remote control applications (16 citations) showcases his ability to combine materials science with practical robotics. With over 145 total citations across his most-cited papers, Guo is recognized for integrating flexible sensors, smart materials, and intelligent control systems—paving the way for more adaptive, touch-sensitive, and autonomously navigating robots in Industry 4.0 environments.

Research Focus

Key Achievements

6
H-Index
8
Papers
145
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Inverse kinematics solution and control method of 6-degree-of-freedom manipulator based on deep reinforcement learning
39 citations · 2024
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 41
🏛 Institutions: Institute for Advanced Study, Shenzhen Institutes of Advanced Technology, Western University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago