Ziyang Shen received his B.S. degree in Microelectronics, Fudan University, Shanghai, China in 2022. He joined Center of Excellence in Biomedical Research on Advanced Integrated-on-chips Neurotechnologies (CenBRAIN Neurotech), Westlake University, Hangzhou, China as a visiting student from Aug. 2021 to Jan. 2022 and is currently a Ph.D. student in CenBRAIN Neurotech.

Ziyang Shen is currently interested in AI Architecture, analog and digital circuit design and deep learning algorithms. He aims at building a real-time system-on-chip based on software and hardware co-design with novel AI architecture and state-of-the-art device technologies. The energy-efficient system is projected for biomedical applications, providing solutions to current predicaments in this field. His recent focus is on new architectures, new device technologies and hardware implementations.

[1] Z. Shen, F. Tian, J. Jiang, C. Fang, X. Xue, J. Yang, and M. Sawan. "NBSSN: A neuromorphic binary single-spike neural network for efficient edge intelligence", 2023 IEEE International Symposium on Circuits and Systems (ISCAS), 2023.

[2] Z. Shen, C. Fang, F. Tian, J. Yang, and M. Sawan. "PN-TMS: Pruned Node-fusion Tree-based Multicast Scheme for Efficient Neuromorphic Systems", 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2023.