Dr Feichi Zhou is now an associate professor at the Southern University of Science and Technology and the principal investigator of the Laboratory of Bioinspired In-Sensor Computing. She has been selected for the National Overseas High-Level Youth Talent Program and is the Chief Scientist of the National Key R&D Program Young Scientist Project. She is also a recipient of the Hong Kong Young Scientist Award. She has been working on bioinspired in-sensor and near-sensor computing devices and systems, optoelectronic memory & neuromorphic vision sensors, emerging devices for the post-Moore's era, AI vision chips, and monolithic 3D integrated sensing-memory-computing chips. She has published more than 60 peer-reviewed papers, including as corresponding or first author in high-impact journals, e.g., Nature Nanotechnology (2 papers), Nature Electronics, and Nature Communications (2 papers). She serves as a reviewer for Nature Electronics, Nature Sensors, Nature Communications, and Science Advances. Additionally, she serves as a Youth Editorial Board Member for journals such as InfoMat, Nano-Micro Letters, and Science Bulletin. 

• Bioinspired in-sensor and near-sensor computing devices and systems

• Optoelectronic memory & neuromorphic vision sensors

• Emerging devices for the post-Moore's era

• AI vision chip

• Monolithic 3D integrated sensing-memory-computing chips

Applied Physics, The Hong Kong Polytechnic University

Advanced Materials Science and Engineering, Imperial College London

Materials Science and Engineering, University of Science and Technology Beijing

Associate Professor, School of Microelectronics, Southern University of Science and Technology

Post-doctoral Fellow, The Hong Kong Polytechnic University 

Hong Kong Young Scientist Award, 2020

Poster Award, Electronic Materials and Devices Workshop, Croucher Foundation, Hong Kong, 2019

Best Paper Award, IEEE International Conference on Electron Devices and Solid-State Circuits, 2018

IEEE Best PhD Thesis Award (Hong Kong Chapter), IEEE/EDSSC, Hong Kong, 2018

Best paper award, International Symposium on Memory Devices for Abundant Data Computing, 2017

Research ID: /

1. Jiayi Xu#, Biyi Jiang#, Weizhen Wang#, Jingkai Qin, Liang Ran, Songhua Cai*, and Feichi Zhou*, “High-Order Dynamics in an Ultra-Adaptive Neuromorphic Vision Device”, Nature nanotechnology, 2025.

2. Feichi Zhou and Yang Chai, “Near-sensor and in-sensor computing”, Nature Electronics, 2020, 3, 664. (ESI highly cited paper).

3. Feichi Zhou, Zheng Zhou, Jiewei Chen, Tsz Hin Choy, Jingli Wang, Ning Zhang, Ziyuan Lin, Shimeng Yu, Jinfeng Kang, H. -S. Philip Wong and Yang Chai*, “Optoelectronic Resistive Random-Access Memory for Neuromorphic Vision Sensors”, Nature Nanotechnology, 2019, 14, 776–782 (2019). (ESI highly cited paper)

4. Pei-Yu Huang#, Bi-Yi Jiang#, Hong-Ji Chen#, Jia-Yi Xu, Kang Wang, Cheng-Yi Zhu, Xin-Yan Hu, Dong Li, Liang Zhen, Fei-Chi Zhou*, Jing-Kai Qin* and Cheng-Yan Xu*, “Neuro-inspired optical sensor array for high-accuracy static image recognition and dynamic trace extraction”, Nature Communications, 2023, 14, 6736.

5. Guangdong Zhou, Jie Li, Qunliang Song, Lidan Wang, Zhijun Ren, Bai Sun, Xiaofang Hu, Wenhua Wang, Gaobo Xu, Xiaodie Chen, Lan Cheng, Feichi Zhou* & Shukai Duan*, “Full Hardware Implementation of Neuromorphic Visual System Based on Multimodal Optoelectronic Resistive Memory Arrays for Versatile Image Processing”, Nature Communications, 2023, 14, 8489. (Editor’s highlight)