Papers
2
Total Citations
45
H-Index
2
About
Xiaoqi Wu is a pioneering researcher at the intersection of artificial intelligence in education and advanced neuromorphic materials. Her work spans two seemingly disparate but equally transformative fields: the human-centered adoption of AI in learning environments and the development of stretchable, brain-inspired electronics. In her highly cited 2023 study, Wu developed an integrated model predicting pupils’ acceptance of artificially intelligent robots as teachers, a critical contribution to understanding how young learners interact with emerging educational technologies. More recently, she has broken new ground in hardware, co-authoring a 2025 study on strain-insensitive, air-stable stretchable carbon nanotube-based synaptic transistors. This work directly addresses a major bottleneck in soft robotics and skin electronics—fabricating high-yield, durable neuromorphic device arrays on elastic substrates. By enabling synaptic transistors that mimic brain activities while remaining stable under mechanical strain, Wu’s research paves the way for truly flexible, intelligent systems. With her work accumulating over 45 citations in just a few years, Wu is establishing herself as a versatile innovator, bridging the gap between human-machine interaction and the physical hardware that will power tomorrow’s adaptive technologies.
Research Focus
Key Achievements
Top Papers
- 1
- 2