Prof. Xiaobing Yan | Neurotechnology | Best Researcher Award

Prof. Xiaobing Yan, Hebei University, China.

Professor Xiaobing Yan is a distinguished researcher specializing in novel memory devices and memristor-based brain-inspired chip technologies. As a Senior Member of IEEE and a reviewer for leading journals, he has made significant contributions to the field of neuromorphic engineering. His outstanding achievements include recognition as a Young Changjiang Scholar and a Young Top-notch Talent under China’s National Ten Thousand Talents Program. With over 120 high-impact publications, 5,600+ citations, and an H-index of 40, he is globally recognized among the top 2% of scientists. His research has been supported by several prestigious national and provincial funding programs.

Profile

Scopus

🎓 Early Academic Pursuits

Xiaobing Yan embarked on his academic journey with a deep passion for electronics and information engineering. His early years were marked by an unwavering dedication to understanding the complexities of memory devices and neuromorphic systems. As he progressed through his studies, his curiosity and drive led him to explore the intersection of artificial intelligence and hardware development. His rigorous academic training laid a solid foundation for his future contributions to next-generation computing technologies.

💪 Professional Endeavors

Currently serving as a Professor at the Institute of Life Science and Green Development, Hebei University, Xiaobing Yan has established himself as a distinguished leader in the field of electronic engineering. He is a Doctoral Supervisor and a Senior Member of IEEE, a testament to his vast expertise and influence in the scientific community. His role extends beyond academia, as he actively engages in national-level research programs and collaborates with top-tier research institutions. His professional journey is a testament to his commitment to pioneering advancements in neuromorphic computing and memristor-based brain-inspired chip technologies.

🤖 Contributions and Research Focus

Xiaobing Yan’s research primarily revolves around novel memory devices and brain-like computing systems. His work has been instrumental in the advancement of memristor-based chip technologies, which hold the potential to revolutionize artificial intelligence hardware. By bridging the gap between neuroscience and semiconductor innovation, he is contributing to the development of energy-efficient, high-performance computing architectures. His research projects, funded by prestigious national programs, aim to push the boundaries of nanoelectronics and intelligent systems.

🏆 Accolades and Recognition

Xiaobing Yan’s groundbreaking work has earned him widespread recognition. In 2019, he was honored as a Young Changjiang Scholar by the Ministry of Education and selected as a Young Top-notch Talent under the National Ten Thousand Talents Program. In 2024, he further cemented his legacy by winning the Excellence Award at the National Disruptive Innovation Technology Competition. His contributions are not only recognized in China but also on a global scale, as he has been listed among the top 2% of scientists worldwide by Stanford University.

🌟 Impact and Influence

With over 120 high-impact publications and more than 5,600 citations, Xiaobing Yan’s research has significantly shaped the field of electronics and artificial intelligence. His H-index of 40 reflects the depth and relevance of his contributions. As a reviewer for prestigious journals such as Nature Electronics, Advanced Materials, and ACS Nano, he plays a crucial role in shaping the direction of cutting-edge research. His influence extends beyond his publications, as he mentors young researchers and fosters collaborations that drive innovation in neuromorphic computing.

🚀 Legacy and Future Contributions

As a leader in disruptive technology and nanoelectronics, Xiaobing Yan is poised to continue pushing the boundaries of scientific discovery. His ongoing research projects, including multiple National Key R&D initiatives and collaborations with leading institutions, demonstrate his commitment to pioneering breakthroughs in brain-inspired computing. With his vision and expertise, he is set to leave a lasting legacy in the development of next-generation intelligent systems, shaping the future of artificial intelligence and semiconductor technology.

Publication

1. In situ training of an in-sensor artificial neural network based on ferroelectric photosensors

   • Authors: H. Lin, Haipeng; J. Ou, Jiali; Z. Fan, Zhen; X. Gao, Xingsen; J. Liu, Junming
   • Year: 2025

 

1. Ultra robust negative differential resistance memristor for hardware neuron circuit implementation

   • Authors: Y. Pei, Yifei; B. Yang, Biao; X. Zhang, Xumeng; S. Li, Shushen; X. Yan, Xiaobing
   • Year: 2025

 

1. Physical unclonable in-memory computing for simultaneous protecting private data and deep learning models

   • Authors: W. Yue, Wenshuo; K. Wu, Kai; Z. Li, Zhiyuan; R. Huang, Ru; Y. Yang, Yuchao
   • Year: 2025

 

1. Memristor-based feature learning for pattern classification

   • Authors: T. Shi, Tuo; L. Gao, Lili; Y. Tian, Yang; X. Yan, Xiaobing; Q. Liu, Qi
   • Year: 2025

 

1. Harnessing spatiotemporal transformation in magnetic domains for nonvolatile physical reservoir computing

   • Authors: J. Zhou, Jing; J. Xu, Jikang; L. Huang, Lisen; X. Yan, Xiaobing; S.T. Lim, Sze Ter
   • Year: 2025

 

1. Flexoelectric Effect in Thin Films: Theory and Applications

   • Authors: X. Jia, Xiaotong; R. Guo, Rui; J. Chen, Jingsheng; X. Yan, Xiaobing
   • Year: 2025

 

1. Deoxyribonucleic acid brick crystals-based memristor as an artificial synapse for neuromorphic computing

   • Authors: Z. Wang, Zhongrong; X. Liu, Xinran; J. Li, Jiahang; J. Lou, Jianzhong; X. Yan, Xiaobing
   • Year: 2025

 

1. Weighted Echo State Graph Neural Networks Based on Robust and Epitaxial Film Memristors

   • Authors: Z. Guo, Zhenqiang; G. Duan, Guojun; Y. Zhang, Yinxing; Y. Faraj, Yousef; X. Yan, Xiaobing
   • Year: 2025

 

1. Achieving over 10 % efficiency in kesterite solar cells via selenium-free annealing

   • Authors: Q. Zhou, Qing; Y. Cong, Yijia; H. Li, Hao; Y. Sun, Yali; W. Yu, Wei
   • Year: 2024

 

1. Hardware implementation of memristor-based artificial neural networks

• Authors: F.L. Aguirre, Fernando L.; A. Sebastian, Abu; M. Le Gallo, Manuel; S. Matias Pazos, Sebastian; M. Lanza, Mario
• Year: 2024

 

Conclusion

Professor Yan’s work plays a pivotal role in advancing memory technology and brain-inspired computing. His extensive research contributions and leadership in high-impact projects underscore his expertise in developing next-generation computing technologies. His global recognition and numerous accolades highlight his influence in the field, positioning him as a key figure in neuromorphic engineering and memory device innovation.