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
Digital Signal Processing, Brain-Machine Interfaces, Biomedical Signal Processing, Healthcare, Embedded System Design, Machine Learning, Deep Learning and Artificial Intelligence.
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
et al., 2022, Hardware-efficient compression of neural multi-unit activity, Ieee Access, Vol:10, ISSN:2169-3536, Pages:117515-117529