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.
et al., 2018, Compact standalone platform for neural recording with real-time spike sorting and data logging., J Neural Eng, Vol:15
et al., 2017, A 64-Channel Versatile Neural Recording SoC With Activity-Dependent Data Throughput, Ieee Transactions on Biomedical Circuits and Systems, Vol:11, ISSN:1932-4545, Pages:1344-1355
et al., 2016, Next Generation Neural Interfaces for low-power multichannel spike sorting, FENS Forum of Neuroscience, FENS
et al., 2016, An Event-Driven SoC for Neural Recording, 12th IEEE Biomedical Circuits and Systems Conference (BioCAS), IEEE, Pages:404-407, ISSN:2163-4025
et al., 2018, Waveform Generator, GB