Title: Associate Research Scientist
Research: Brain Machine Interfaces / Brain Computer Interfaces
Tel: (8610)5880 2060
Address: Xinjiekouwai Street 19, Beijing Normal University, Yingdong Building
Postcode: 100875
Email: lz bnu edu cn

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Curriculum vitae

Research Interests
My main research interests are in brain-machine interface (brain-computer interface) technologies and related neuroscience questions. Particularly, I am interested in decoding algorithms and signal processing methods for implanted electrode motor-cortical brain-machine interfaces. I also want to build improved models of neural encoding for intended upper-limb movements and better understand the process of learning to use a brain-machine interface. More broadly, I am also interested in decoding for other neural interface modalities, particularly functional near infrared spectroscopy.

Educational Background
2004/08 - 2010/05, Duke University, Ph.D. in Computer Science, Advisor: Craig S. Henriquez
2001/01 - 2004/05, Purdue University, B.S. in Computer Science and Mathematics

Employment History
2013/03 - current, Beijing Normal University, School of Brain and Cognitive Sciences, Associate Research Scientist
2011/03 - 2012/12, Duke University, Postdoctoral Associate, Advisor: Miguel A. L. Nicolelis
2010/06 - 2011/02, Duke University, Research Scholar, Advisor: Miguel A. L. Nicolelis

Selected Publications
Li J, Chen X, & Li Z. (2019) Spike detection and spike sorting with a hidden Markov model
improves offline decoding of motor cortical recordings. Journal of Neural Engineering. 16:016014.
doi:10.1088/1741-2552/aaeaae  Code pack

Li J & Li Z. (2017) Sums of Spike Waveform Features for Motor Decoding. Frontiers in
. 11:406. doi: 10.3389/fnins.2017.00406

Li Z, Jiang Y-H, Duan L, & Zhu C-Z. (2017) A Gaussian mixture model based adaptive classifier for fNIRS brain-computer interfaces and its testing via simulation. Journal of Neural Engineering. 14:4. doi:10.1088/1741-2552/aa71c0 MATLAB Code

Li S, Li J, & Li Z. (2016) An Improved Unscented Kalman Filter Based Decoder for Cortical Brain-Machine Interfaces. Frontiers in Neuroscience. 10:587. doi: 10.3389/fnins.2016.00587  MATLAB Code

Li Z. (2014) Decoding methods for neural prostheses: where have we reached? Frontiers in Systems Neuroscience. 8:129. doi: 10.3389/fnsys.2014.00129

Schwarz DA, Lebedev MA, Hanson TL, Dimitrov DF, Lehew G, Meloy J, Rajangam S, Subramanian V, Ifft PJ, Li Z, Ramakrishnan A, Tate A, Zhuang KZ, & Nicolelis MA. (2014) Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys. Nature Methods. 11(6):670-6. doi:10.1038/nmeth.2936
Ifft PJ, Shokur S, Li Z, Lebedev MA, & Nicolelis MAL. (2013) A Brain-Machine Interface Enables Bimanual Arm Movements in Monkeys. Science Translational Medicine. 5, 210ra154. doi:10.1126/scitranslmed.3006159
O'Doherty JE, Lebedev MA, Li Z, & Nicolelis MAL. (2012) Virtual active touch using randomly patterned intracortical microstimulation. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 20(1), 85-93. doi:10.1109/TNSRE.2011.2166807
Li Z, O'Doherty JE, Lebedev MA, & Nicolelis MAL. (2011) Adaptive Decoding for Brain-Machine Interfaces Through Bayesian Parameter Updates. Neural Computation. 23(12), 3162-3204. doi:10.1162/NECO_a_00207
Li Z, O'Doherty JE, Hanson TL, Lebedev MA, Henriquez CS, & Nicolelis MAL. (2009) Unscented Kalman filter for brain-machine interfaces. PLoS ONE. 4(7): e6243. doi:10.1371/journal.pone.0006243