Researcher | Guangdong University of Technology | China
Dr. Ni Yao is a distinguished researcher at the Guangdong University of Technology, Guangzhou, China, widely recognized for his contributions to advanced materials, neuromorphic engineering, and intelligent sensing–processing systems. With an interdisciplinary focus spanning materials science, flexible electronics, artificial intelligence hardware, and intelligent control mechanisms, his research advances next-generation photonic synaptic transistors, in-sensor reservoir computing architectures, and flexible neuromorphic devices capable of multidimensional shape morphing. Dr. Yao has authored 65 peer-reviewed publications, achieved 1,679 citations, and maintains an h-index of 23, reflecting the depth, continuity, and global influence of his scholarly work. His recent high-impact contributions include crystallized conjugated polymer-based photonic synaptic transistors, paper-based perovskite artificial neuromorphic retinas, free shape-morphing neuromorphic devices published in Nature Communications, as well as novel methodologies for industrial control deadlock avoidance, frequency-aware transformers for pipeline leak detection, and symmetric optimization models for delivery duration forecasting. Engaging in collaborations with over 160 co-authors, Dr. Yao actively contributes to multidisciplinary research communities, promoting scientific advancement across materials innovation, industrial automation, computational sensing, and AI-driven systems engineering. His work delivers broad societal impact by enabling energy-efficient intelligent devices, enhancing autonomous perception capabilities, and driving innovations that support safer, more sustainable, and technologically advanced industrial ecosystems. Through continuous innovation, rigorous scholarship, and extensive international collaboration, Dr. Ni Yao remains at the forefront of shaping future directions in intelligent materials, neuromorphic computing, and integrated sensing technologies.
Profiles: Scopus | ORCID | ResearchGate
Featured Publications
1. Wei, H., Yang, J., Fu, C., Li, Z., Ni, Y., Wang, B., He, B., Jiang, S., & He, G. (2025). ALD-driven ultra-thin ZnO channels for flexible electrolytic neuromorphic devices. IEEE Electron Device Letters.
2. Ni, Y., Zhang, Y., Lin, J., Liu, X., Yu, Y., Liu, L., Zhong, W., Chen, Y., Chen, R., Kwok, H. S., et al. (2025). Transistor-structured artificial dendrites for spatiotemporally correlated reservoir computing. IEEE Electron Device Letters.
3. Guan, X., Wu, W., & Ni, Y. (2025). A novel methodology to deadlock analysis and avoidance for automatic control systems based on Petri Net. Processes, 13(10).
4. Chen, M., Lu, Y., Wu, W., Ye, Y., Wei, B., & Ni, Y. (2025). Multi-scale frequency-aware transformer for pipeline leak detection using acoustic signals. Sensors, 25(20).
5. Ji, Z., Liu, J., He, Y., Yang, H., Zhang, L., Guan, S., Ni, Y., & Wu, T. (2025). Stretchable synaptic device with photonic–electric dual mode for sign language recognition. Advanced Materials Technologies
