02/2023 –present Associate Professor, School of Clinical Medicine, Tsinghua University

10/2019 – 01/2023 Assistant Professor, Dept. of Mechanical Engineering, Tsinghua University

01/2018 – 03/2018 Visiting Scholar, Keck Medical School, University of Southern California

07/2017 – 10/2019 Postdoctoral Fellow, Dept. of Mechanical Engineering, Tsinghua University

Medical engineering; AI supported data analysis; Bio-signal processing; Brain computer interface; Medical robotics; Neurorehabilitation; Precision medicine.

Selected publications (* Corresponding Author, # Co-first Author)

1. Sun, J., Jia, T., Lin, P. J., Li, Z., Ji, L., & Li, C*. (2024). Multiscale Canonical Coherence for Functional Corticomuscular Coupling Analysis. IEEE Journal of Biomedical and Health Informatics, 28(2), 812-822.

2. Li, W., Li, C.*, Liu, A., Lin, P. J., Mo, L., Zhao, H., ... & Ji, L. (2023). Lesion-specific cortical activation following sensory stimulation in patients with subacute stroke. Journal of NeuroEngineering and Rehabilitation, 20(1), 155.

3. Li, Z., Li, W., Lin, P. J., Jia, T., Ji, L., & Li, C.* (2023). Motor-Respiratory Coupling Improves Endurance Performance during Rhythmic Isometric Handgrip Exercise. Medicine and Science in Sports and Exercise, 10-1249.

4. Jia, T.#, Li, C#,*, Mo, L., Qian, C., Li, W., Xu, Q., Pan, Y., Liu, A.*, & Ji, L*. (2023). Tailoring brain–machine interface rehabilitation training based on neural reorganization: towards personalized treatment for stroke patients. Cerebral Cortex, 33(6), 3043-3052.

5. Sun, J.^#, Jia, T.^#, Li, Z., Li, C*, & Ji, L. (2023). Enhancement of EEG-EMG coupling detection using corticomuscular coherence with spatial-temporal optimization. Journal of Neural Engineering, 20(3), 036001.

6. Lin, P. J., Zhai, X., Li, W., Li, T., Cheng, D., Li, C*, Pan, Y. *, & Ji, L. (2022). A transferable deep learning prognosis model for predicting stroke patients' recovery in different rehabilitation trainings. IEEE Journal of Biomedical and Health Informatics, 26(12), 6003-6011.

7. Li, W., Luo, F., Xu, Q., Liu, A., Mo, L., Li, C*, & Ji, L. (2022). Brain oscillatory activity correlates with the relief of post-stroke spasticity following focal vibration. Journal of Integrative Neuroscience, 21(3), 96.

8. Jia, T., Li, C*, Mo, L., Qian, C., Ji, L., & Liu, A*. (2022). Recognizing the individualized sensorimotor loop of stroke patients during BMI-supported rehabilitation training based on brain functional connectivity analysis. Journal of Neuroscience Methods, 378, 109658.

9. Li, W; Li, C*; Liu, P; Li, Y; Xiang, Y; Jia, T., Xu, Q*; Ji, L. (2021). Development and Preliminary Validation of a Pneumatic Focal Vibration System to the Mitigation of Post-Stroke Spasticity, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29:380-388.

10. Lin, P. J., Jia, T., Li, C*, Li, T., Qian, C., Li, Z., Pan, Y.*, & Ji, L. (2021). CNN-Based Prognosis of BCI Rehabilitation Using EEG From First Session BCI Training. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 1936-1943.

11. Qian, C., Li, W., Jia, T., Li, C.*, Lin, P. J., Yang, Y., & Ji, L. (2021). Quantitative assessment of motor function by an end-effector upper limb rehabilitation robot based on admittance control. Applied Sciences, 11(15), 6854.

12. Li, W., Xu, Q., Li, Y., Li, C.*, Wu, F., & Ji, L. (2021). EEG characteristics in “eyes-open” versus “eyes-closed” condition during vibrotactile stimulation. Biomedical Signal Processing and Control, 68, 102759.

13. Jia, T., Liu, K., Qian, C., Li, C.*, & Ji, L. (2020). Denoising algorithm for event-related desynchronization-based motor intention recognition in robot-assisted stroke rehabilitation training with brain-machine interaction. Journal of Neuroscience Methods, 346, 108909.

14. Xu, Q.^#, Li, C. ^#, Pan, Y.*, Li, W., Jia, T., Li, Z., Ma, D., Pang, X., & Ji, L*. (2020). Impact of smart force feedback rehabilitation robot training on upper limb motor function in the subacute stage of stroke. NeuroRehabilitation, 47(2), 209-215.

15. Jia, T., Liu, K., Lu, Y., Liu, Y., Li, C.*, Ji, L., & Qian, C. (2020). Small-Dimension Feature Matrix Construction Method for Decoding Repetitive Finger Movements From Electroencephalogram Signals. IEEE Access, 8, 56060-56071.

16. Li C. ^#, Jia T. ^#, Xu Q., Ji L.*, Pan Y*. (2019). Brain-computer interface channel-selection strategy based on analysis of event-related desynchronization topography in stroke patients. Journal of Healthcare Engineering, 2019:1-12.

17. Li W, Li C, Xiang Y, Ji L*, Hu H, Liu Y. (2019). Study of the activation in sensorimotor cortex and topological properties of functional brain network following focal vibration in healthy subjects and subacute stroke patients: an EEG Study. Brain research, 1722, 146338.

18. Li, C*, Rusak, Z., Horvath, I., Kooijman, A., & Ji, L. (2017). Implementation and validation of engagement monitoring in an engagement enhancing rehabilitation system. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(6), 726-738.

19. Li, C*, Rusák, Z., Horváth, I., & Ji, L. (2016). Development of engagement evaluation method and learning mechanism in an engagement enhancing rehabilitation system. Engineering Applications of Artificial Intelligence, 51, 182-190.

20. Li, C*, Rusák, Z., Horváth, I., & Ji, L. (2016). Validation of the reasoning of an entry-level cyber-physical stroke rehabilitation system equipped with engagement enhancing capabilities. Engineering Applications of Artificial Intelligence, 56, 185-199.

Awards and Membership

1. Awardee, 5th Young Elite Scientists Sponsorship Program by China Association for Science and Technology, 2019.

2. Awardee, Beijing Nova Program by Beijing Municipal Science & Technology Commission, 2023