Imperial College London


Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Research Postgraduate



zheng.zhang18 Website CV




B422Bessemer BuildingSouth Kensington Campus






Zheng Zhang received the B.E degree in Internet of Things from Beijing University of Technology (BJUT), China, and University College Dublin (UCD), Ireland, with GPA: 4.17/4.2,  in 2018, and he was awarded as top 10 graduates of BJUT (Only two qualified undergraduate students). He received the M.S. degree in Communications and Signal Processing from Imperial College London , UK,with distinction in 2019. Since October 2019, he has been working in Next Generation Neural Interfaces (NGNI) Lab, Imperial College London, UK, as a PhD student.

PhD Thesis TOPIC

Low complexity algorithm and ultra-low power hardware for neural signal processing and decoding

Research interests

Digital Signal Processing, Brain-Machine Interfaces, Biomedical Signal Processing, Healthcare, Embedded System Design, Machine Learning, Deep Learning and Artificial Intelligence.



Zhang Z, Feng P, Oprea A, et al., 2023, Calibration-free and hardware-efficient neural spike detection for brain machine interfaces, Ieee Transactions on Biomedical Circuits and Systems, ISSN:1932-4545, Pages:1-17

Zhang Z, Constandinou TG, 2023, Firing-rate-modulated spike detection and neural decoding co-design., J Neural Eng, Vol:20

Zhang Z, Constandinou TG, 2023, Firing-rate-modulated spike detection and neural decoding co-design

Savolainen OW, Zhang Z, Constandinou TG, 2022, Ultra Low Power, Event-Driven Data Compression of Multi-Unit Activity

Savolainen O, Zhang Z, Feng P, et al., 2022, Hardware-efficient compression of neural multi-unit activity, Ieee Access, Vol:10, ISSN:2169-3536, Pages:117515-117529

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