1. Neural engineering 

2. Brain machine interface

Ph.D.,  Biomedical engineering, the University of Texas at Austin, United States, 2019

M.S., Mechanical engineering, University of Michigan at Dearborn, United States, 2015

B.S., Thermal engineering,  Xi'an Jiaotong University, China, 2013.  

   

1.      H Zhu, X Li, L Sun, F He, Z Zhao, L Luan, NM Tran, C Xie. “Clustering with Fast, Automated and Reproducible assessment applied to longitudinal neural tracking”. International conference on machine learning. arXiv: 2003.08533. 2020.

2.      F He, C Sullender, H Zhu, M Williamson, X Li, Z Zhao, T Jones, C Xie, A Dunn and L Luan “Multimodal mapping of neural activity and cerebral blood flow reveals long-lasting neurovascular dissociations after small-scale strokes”, in press, Science Advances, 2020

3.      Z Zhao, X Li, F He, X Wei, S Lin and C Xie, “Parallel, minimally-invasive implantation of ultra-flexible neural electrode arrays”, Journal of Neural Engineering, 2019

4.      CT Sullender, X Li, Z Zhao, H Zhu, X Wei, C Xie and AK Dunn, “Nanoelectronics enabled chronic multimodal neural platform in a mouse ischemic model”, Journal of Neuroscience Methods, 2018

5.      X Wei*, L Luan*, Z Zhao*, X Li, H Zhu, O Potnis and C Xie, “Nanofabricated ultra-flexible electrode arrays for high-density intracortical recording”, Advanced Science, *equal contribution, 2018

6.      Z Zhao, L Luan, X Wei, H Zhu, X Li, S Lin, JJ Siegel, RA Chitwood, C Xie “Nanoelectronic Coating Enabled Versatile Multifunctional Neural Probes”, Nano Letters, 2017

7.      B Amoozgar, X Wei, J Lee, M Bloomer, Z Zhao, P Coh, F He, L Luan, C Xie, Y Han “A novel flexible microfluidic meshwork to reduce fibrosis in glaucoma surgery” PloS One, 2017

8.      L Luan*, X Wei*, Z Zhao*, JJ Siegel, O Potnis, CA Tuppen, S Lin, S Kazmi, RA Fowler, S Holloway, AK Dunn, RA Chitwood, C Xie ”Ultraflexible nanoelectronic probes form reliable, glial scar–free neural integration” Science Advances, *equal contribution, 2017

9.      Z Zhao, MA Ameen, K Duan, G Ghosh* and JF Lo* “On chip Porous Microgel Generation and Microfluidic Enhanced VEGF Detection” Biosensors and Bioelectronics. 2015.

10.   R Liu*, Z Zhao*, A Argento, Q Fang, JF Lo, “Compact Non-invasive Frequency Domain Lifetime Deifferentiation of Type I vs. III Collagen.” Sensors and Actuators B. *equal contribution, 2015.

11.   Z Li, D Hu, Z Zhao, M Zhou, LP Lee, JF Lo, “Balancing Diffusion and Convection in a Spiral Oxygen Gradient Modulates Fibroblast VEGF.” Biomedical Microdevices. 2014.

12.   Q Yang, Z Zhao, Ben Q. Li and Y Ding, “Numerical Analysis of the Rayleigh-Taylor Instability in an Electric Field” Journal of Fluid Mechanics 2015.

13.   JF Lo, Y Wang, Z Li, Z Zhao, D Hu, DT Eddington, J Oberholzer, “Quantitative and Temporal Control of Oxygen Microenvironment at the Single Islet Level,” Journal of Visualized Experiments. 2013.

14.   Z Li, Z Zhao, JF Lo, “Rapid Prototyping of Multiphase Microfluidics with Robotic Cutters” Proc. of SPIE. International Society for Optical Engineering, 2014.

   

1.      JF Lo, Z Zhao, R Liu “Frequency Domain Discrimination of Tissue Proteins” US Patent 10359414B2

2.      C Xie, L Luan, Z Zhao, X Wei “System and Method for Making and Implanting High-Density Electrode Arrays” International Patent App WO2019051163A1 

Our lab is aiming to systemically develop a stable, chronic and high bandwidth neural interface by taking advantages of micro/nano fabrication technology and novel materials. The technical platform we developed will be applied in basic neuroscience research, studying and intervening neurological diseases, and to create seamless brain-machine interface.    

Main research direction:   

Stable, chronic and high bandwidth brain-machine interface and its clinical applications  

Through creating a real-time information transferring channel between the brain and the external machine, invasive brain-machine interface (BMI) is able to restore sensory and motor functions in paralyzed patients, treat systemic neurological diseases, and even bring human-machine integration and the enhancement of the human boundaries to reality. BMI is at the frontier of active neuroscience research and intellectual technologies. However, two restraining problems remain to be solved: 1) the biocompatibility of the implant, and 2) the signal transmission bandwidth at the interface. Conventional neural electrodes cannot be chronically stable when implanted in the brain tissue, and the signals detected gradually fade over time. This causes the electrodes to be short-lived, whilst tremendous training and constant re-calibration is required for a complex neural signal decoding system. On the other hand, current clinically approved electrodes consist up to a couple hundred channels, limited information is extracted for a low-resolution control and precision in their application.  

Our group aim to develop next-generation large-scale electrode array that consists thousands of channels and are chronically stable, in order to break through the aforementioned restrains and enhance the clinical application of brain probes. With that technical strength, we aim to retore high-performance movement in spinal cord injured, paralyzed patients and achieve high-resolution perception reconstruction for perception impaired patients.    

The study, diagnosis, and treatment of neurological diseases by large-scale electrophysiology 

Neurological diseases, in particular neurodegenerative diseases such as Parkinson’s and Alzheimer’s disease, are often accompanied with the long-term progression of the disease pathology. It is difficult to chronically monitor the changes in the brain structures and functions during the disease progression via existing techniques. However, large-scale ultra-flexible electrode arrays perform stably during long-term measurements; it can not only resolve high-resolution abnormalities in the distorted local neural circuits, but also monitor multiple functional regions of the disease brain model on the functional network level. It provides a more direct, higher resolution and more enriched tool for the research in pathology, by enabling electrophysiological measurement with single neuron resolution in thousands of neurons across multiple brain regions. Furthermore, this technical platform can be applied to the pathological study of other neurological diseases such as epilepsy, stroke, or psychiatric disorders. Our group aim to transfer the advantages on large-scale electrophysiology to investigate the disease pathology and progression of major brain diseases, and intervene and treat the disease by precisely manipulate the abnormal neurological systems through electrical stimulation.    

Integrated system of flexible neural interface  

The development of systemic neural interface involves not only the front-end electrode array, but also efficient surgical implantation device and integrated data acquisition system. With a multidisciplinary background of various engineering and experience in deep collaboration with fundamental neuroscience research teams, our lab is actively looking to develop and promote the technical integration and advancement, to further promote the application of the next-generation ultra-flexible neural interface in basic research of neuroscience as well as in the clinical setup.