Imperial College London


Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Academic Visitor



yan.liu06 CV




Electrical EngineeringSouth Kensington Campus






Dr Yan Liu currently is an associate professor in Shanghai Jiaotong university (PWP in SJTU), he is also a visiting academic in Centre of Bio-inspired Technology, Department of Electrical and Electronic, Imperial College. He was working within Next Generation Neural Interfaces (NGNI) Lab during his postdoc research in Imperial College, and involved in CANDO , iProbe, NGNI, I2MOVE and Senseback projects.

His research interest includes low power mixed-signal integrated circuits, biomedical circuits and systems, Lab-on-chip.


Dr Yan Liu received the B.Eng degree in 2006 from Zhejiang University, China, the M.Sc degree in 2007 and Ph,D in 2012 from Electrical and Electronic Engineering at Imperial College London, UK. From 2012 to 2019 he was a research associate and research fellow with NGNI lab. Since 2020 he is an associate professor in Shanghai Jiaotong university



Liu H, Guo T, Yan P, et al., 2022, A Hybrid 1<sup>st</sup>/2<sup>nd</sup>-Order VCO-Based CTDSM With Rail-to-Rail Artifact Tolerance for Bidirectional Neural Interface, Ieee Transactions on Circuits and Systems Ii: Express Briefs, Vol:69, ISSN:1549-7747, Pages:2682-2686

Chen Y, Liu Y, Li Y, et al., 2022, An Energy-Efficient ASK Demodulator Robust to Power-Carrier-Interference for Inductive Power and Data Telemetry., Ieee Trans Biomed Circuits Syst, Vol:16, Pages:108-118

Huang J, Zhou T, Liu H, et al., 2022, Low-Noise, High-Linearity Sine-Wave Generation Using Noise-Shaping Phase-Switching Technique, Ieee Transactions on Instrumentation and Measurement, Vol:71, ISSN:0018-9456

Pan L, Chen M, Chen Y, et al., 2021, An Energy-Autonomous Power-and-Data Telemetry Circuit With Digital-Assisted-PLL-Based BPSK Demodulator for Implantable Flexible Electronics Applications, Ieee Open Journal of Circuits and Systems, Vol:2, Pages:721-731

Luo J, Firflionis D, Turnball M, et al., 2020, The neural engine: a reprogrammable low power platform for closed-loop optogenetics, Ieee Transactions on Biomedical Engineering, Vol:67, ISSN:0018-9294, Pages:3004-3015

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