Summary
Song Luan received the M.Sc. in analogue and digital integrated circuit design and Ph.D. degrees in biomedical microelectronics engineering from Imperial College London in 2010 and 2014 respectively.In 2014, he works as a research associate in the Next Generation Neural Interfaces Lab.
He has designed different types of integrated neural stimulation circuits and systems with 0.35 and 0.18 um process. He is also an advanced engineer in PCB, firmware and software development for in-house custom hardware.
His main research interests include chronic implantable neural interfaces and its applications, low power microelectronics and wireless power/data link.
Publications
Journals
Williams I, Brunton E, Rapeaux A, et al., 2020, SenseBack-an implantable system for bidirectional neural interfacing, Ieee Transactions on Biomedical Circuits and Systems, Vol:14, ISSN:1932-4545, Pages:1079-1087
Luan S, Williams I, Maslik M, et al., 2018, Compact standalone platform for neural recording with real-time spike sorting and data logging, Journal of Neural Engineering, Vol:15, ISSN:1741-2552, Pages:1-13
Liu Y, Luan S, Williams I, et al., 2017, A 64-Channel Versatile Neural Recording SoC with Activity Dependant Data Throughput, Ieee Transactions on Biomedical Circuits and Systems, Vol:11, ISSN:1932-4545, Pages:1344-1355
Conference
Luan S, Liu Y, Williams I, et al., 2017, An Event-Driven SoC for Neural Recording, IEEE Biomedical Circuits and Systems (BioCAS) Conference, IEEE, Pages:404-407
Patents
Williams I, Rapeaux A, Luan S, et al., 2018, Waveform Generator, GB