• 南开大学高端人才岗位英才教授（三级教授，2025-）

• 国家重点研发计划项目首席科学家（2024-）

• 教育部首批中央高校优秀青年团队负责人（2023-）

• “可信行为智能算法与系统”教育部工程研究中心副主任（2022-）

• 入选南开大学“青年学科带头人培养计划”（2021-2024）

• 2019.12-至今, 南开大学, 人工智能学院, 教授，博士生导师
  

• 2012.07-2019.12, 南开大学, 人工智能学院, 副教授，硕士生导师
  

• 2011.05-2012.06, 瑞士苏黎世联邦理工学院 (ETH Zurich), 生物力学研究所, 博士后

• 2005.09-2011.03, 瑞士苏黎世联邦理工学院 (ETH Zurich), 机器人与智能系统研究所, 博士

  （期间：在苏黎世神经科学中心辅修神经科学博士课程）

• 2003.09-2005.08, 香港科技大学, 电机与电子工程系, 硕士

• 1999.09-2003.06, 天津大学, 精密仪器与光电子工程学院, 学士

热烈欢迎加入本团队开展博士后研究、攻读博士和硕士研究生、进行科研实习和创新！

我们的研究面向世界科技前沿、面向人民生命健康，我们有充足的科研项目和经费支撑，有先进的仪器设备与平台，有密切的医工合作、国内外合作，这将为你的科研梦想插上飞翔的翅膀！

主持国家级科研项目  

• 国家重点研发计划“智能机器人”重点专项项目：脑肢融合、人在回路的脑功能重塑机器人系统与临床应用研究（2024YFB4709900），主持.

• 国家自然科学基金重点项目：脑躯融合干预、仿生运动辅助的外肌肉躯干康复机器人研究 (U24A20284)，主持.

• 国家自然科学基金面上项目：面向TMS靶向神经调控的脑肌功能网络分解与机器人双臂协作多靶点主动导航定位方法研究 (62473214)，主持.

• 国家自然科学基金重点项目：脑肢协同多模态干预的脑卒中专科型手部康复机器人 (U1913208)，主持（已结题）.

• 国家重点研发计划“智能机器人”重点专项课题：基于骨愈合机理的主被动融合量化康复 (2018YFB1307803)，主持（已结题）.

• 国家自然科学基金面上项目：面向偏瘫患者步行康复训练的柔索机器人动态规划与控制方法研究 (61873135)，主持（已结题）.

• 国家自然科学基金国际合作重点项目：康复机器人主动自适应控制策略与在线评价方法研究与应用 (61720106012)，主持课题（已结题）.

• 国家自然科学基金青年项目：基于fMRI脑功能成像的机器人辅助腕手神经康复训练与评价方法研究（61403215），主持（已结题）.

• 中国工程院战略咨询重点项目课题：可信行为智能技术体系研究（23-HZ-18-02），主持（已结题）

医工合作、国内外合作

• 医工合作：北京天坛医院，中国人民解放军总医院，中国康复研究中心，南开大学第一附属医院（天津市人民医院），天津市环湖医院，等

• 国内外合作：瑞士ETH Zurich，香港科技大学，等
  

主要奖励

本课题组多次获得国内外奖励，研究生获得多项国家奖学金、优秀毕业生等奖励和荣誉，并在学生竞赛和创新项目中多次获奖:              

学术获奖：

• 2026.04, 2025年天津市自然科学二等奖（排名第一）：“面向神经康复的脑-肌-肢功能量化分析方法与应用”

• 2026.04, 最佳学生论文奖（通讯作者）, The 12th International Conference on Electrical Engineering, Control and Robotics

• 2025.11, 中国智能机器人学术新星奖
  

• 2024.12, 最佳学生论文奖（通讯作者）, International Conference on Computers and Artificial Intelligence Technology

• 2024.09, 领跑者5000-中国精品科技期刊顶尖学术论文奖（通讯作者）
  

• 2023.12, 国家卫健委第三届医学科技创新大赛二等奖：“智疗-脑肢融合的帕金森病全周期智能诊疗辅助系统”

• 2023.12, 最佳会议论文奖, The 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)
  

• 2021.07, 最佳会议论文提名奖（通讯作者）, IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems

• 2021.04, 中国人工智能与机器人开发者大会技术突破明珠奖

• 2019.11, 《仪器仪表学报》年度优秀论文奖（通讯作者）

• 2017.01, 《智能系统学报》第三届优秀论文奖（通讯作者）

• 2016.08, 最佳先进机器人论文提名奖（通讯作者）, IEEE International Conference on Advanced Robotics and Mechatronics

• 2015.06, 最佳会议论文提名奖（通讯作者）, IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems

学生竞赛和创新项目获奖（指导教师）：

• 2023.12, 首届全国人工智能应用场景创新挑战赛全国总决赛一等奖

• 2022.12, 中国高校计算机大赛-智能交互创新赛三等奖

• 2022.12, 第八届中国国际“互联网+”大学生创新创业大赛天津赛区高教主赛道银奖

• 2021.10, 第七届中国国际“互联网+”大学生创新创业大赛天津赛区高教主赛道金奖、全国总决赛铜奖

• 2021.10, 中美青年创客大赛天津赛区第一名
  

• 2017.07, 第七届“华为杯”全国大学生智能设计竞赛三等奖
  

• 2016.05, 南开大学本科生创新科研计划优秀项目二等奖

• 2015.08, 第五届“华为杯”全国大学生智能设计竞赛一等奖

• 2015.08, 第五届“华为杯”全国大学生智能设计竞赛二等奖

（1）脑肢失能溯源分析与量化诊断

1. Lu J, Ge Q, Liu Y, He J*, Han J*, Yu N*(于宁波). Awareness- and Arousal-specific Brain Analysis Predicts Spinal Cord Stimulation Effectiveness in Disorders of Consciousness. IEEE Journal of Biomedical and Health Informatics, 2026: 1-14. https://doi.org/10.1109/JBHI.2026.3677372

2. Han, J., Lu, J., Lin, J., Zhang, S., Yu, N.*(于宁波). A functional region decomposition method to enhance fNIRS classification of mental states. IEEE Journal of Biomedical and Health Informatics, 2022, 26(11), 5674-5683. https://doi.org/10.1109/JBHI.2022.3201111

3. Qi, H., Zhao, H., Li, E., Lu, X., Yu, N.*(于宁波), Liu, J. *, Han, J.*. DeepQA: a unified transcriptome-based aging clock using deep neural networks. Aging Cell, 2025, 24(5), e14471. https://doi.org/10.1111/acel.14471 

4. Lu, J., Zhang, X., Shu, Z., Han, J., Yu, N.*(于宁波). A dynamic brain network decomposition method discovers effective brain hemodynamic sub-networks for Parkinson's Disease. Journal of Neural Engineering, 2024, 21(2), 026047. https://doi.org/10.1088/1741-2552/ad3eb6 

5. Lu, J.#, Wang, Y.#, Shu, Z., Zhang, X., Wang, J., Cheng, Y., Zhu, Z., Yu, Y., Wu, J.*, Han, J.*, Yu, N.*(于宁波). fNIRS-based brain state transition features to signify functional degeneration after Parkinson's disease. Journal of Neural Engineering, 2022, 19(4), 046038. https://doi.org/10.1088/1741-2552/ac861e 

6. You, Y., Lin, J., Zhang, S., Huo, W., Han, J.*, Yu, N.*(于宁波). An adaptive oscillator-driven gait phase model for continuous motion estimation across speeds. IEEE Transactions on Instrumentation and Measurement, 2024, 73, 1-14. https://doi.org/10.1109/TIM.2024.3381303

7. Zeng, Q.#, Liu, P.#, Yu, N.#(于宁波), Wu, J.*, Huo, W.*, Han, J.*. Video-based quantification of gait impairments in Parkinson's disease using skeleton-silhouette fusion convolution network. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023, 31, 2912-2922. https://doi.org/10.1109/TNSRE.2023.3291359 

8. You, Y., Lin, J., Zhang, X., Lu, J., Yu, N.*(于宁波), Han, J. Reconstruction and dynamic analysis of corticomuscular subnetworks reveal task-specific neural coordination in visuomotor control. Journal of Neuroscience Methods, 2026, 426, 110640. https://doi.org/10.1016/j.jneumeth.2025.110640 

9. Liu, P.#, Yu, N.#, Yang, Y., Yu, Y., Sun, X., Yu, H., Han, J.*, Wu, J.*(于宁波). Quantitative assessment of gait characteristics in patients with Parkinson's disease using 2D video. Parkinsonism & Related Disorders, 2022, 101, 49-56. https://doi.org/10.1016/j.parkreldis.2022.06.012 

10. Sun, Y.#, Liang, S.#, Yu, Y., Yang, Y., Lu, J., Wu, J., Cheng, Y., Wang, Y., Wu, J.*, Han, J.*, and Yu, N.*(于宁波). Plantar pressure-based temporal analysis of gait disturbance in idiopathic normal pressure hydrocephalus: Indications from a pilot longitudinal study. Computer Methods and Programs in Biomedicine, 2022, 217, 106691. https://doi.org/10.1016/j.cmpb.2022.106691 

（2）康复机器人高相容设计与非线性鲁棒控制

1. Zou W, Chen X, Li S, Duan P, Yu N*（于宁波）, Shi L. Robust admittance control for human arm strength augmentation with guaranteed passivity: a complementary design. IEEE/ASME Transactions on Mechatronics, 2022, 27(6): 5936-5947. https://doi.org/10.1109/TMECH.2022.3191469 

2. Wang X, Fang Y, Yu N*（于宁波）, Han J*. Barrier Function-Based Adaptive Control of Twisted Tendon-Sheath Actuated System with Unknown Rigi-Flexible Coupling for Robotic Ureteroscopy. IEEE/ASME Transactions on Mechatronics, 2024, 29(3): 2362-2372. https://doi.org/10.1109/TMECH.2023.332805

3. Wang X, Fang Y, Yu N*（于宁波）, Han J*. A practical output feedback controller for robotic flexible endoscope system with unknown dynamics and actuator uncertainties. IEEE/ASME Transactions on Mechatronics, 2025, 30(4): 2889-2899. https://doi.org/10.1109/TMECH.2025.3569275 

4. X. Wang#, N. Yu#（于宁波）, J. Han, Y. Fang. Modeling and Robust Control for Tendon–Sheath Artificial Muscle System Twist with Time-Varying Parameters and Input Constraints: An Exploratory Research. IEEE Transactions on Industrial Electronics, 2023, 70(1): 878-887. https://doi.org/10.1109/TIE.2021.3134084 

5. X. Wang#, N. Yu#（于宁波）, Han J, Fang Y. Modeling and adaptive control for tendon sheath artificial muscle actuated bending-tip systems with unknown parameters and input hysteresis: An experimental research. IEEE Transactions on Industrial Electronics, 2023, 70(10): 10588-10597. https://doi.org/10.1109/TIE.2022.3219105 

6. X. Wang#, N. Yu#（于宁波）, Bie D, Han J, Fang Y. A novel ESMF-based observer and control scheme for a type of tendon-sheath hysteresis system. Automatica, 2021, 131: 109800. https://doi.org/10.1016/j.automatica.2021.109800 

7. Wu Y, Han J, Bai X, Lin J, Yu N*（于宁波）. A sensitivity-guided unsupervised learning method for image reconstruction of electrical impedance tomography. IEEE Transactions on Instrumentation and Measurement, 2025, 74: 1-12. https://doi.org/10.1109/TIM.2025.3555752 

8. Wu Y, Bai X, Lu J, Han J, Yu N*（于宁波）. A Generative Model-Enhanced Deep Image Prior Framework for Unsupervised 3-D Electrical Impedance Tomography. IEEE Transactions on Instrumentation and Measurement, 2026, 75: 1-15. https://doi.org/10.1109/TIM.2026.3677975

9. Zhou Z, Hao L, Zheng H, Wang X, Lu J, Han J, Yu N*（于宁波）. Design and nonlinear control of an orthopedic rehabilitation robot to accelerate fracture healing. IEEE Transactions on Medical Robotics and Bionics, 2025: 1-11. https://doi.org/10.1109/TMRB.2025.3646754 

10. Hao L, Zhou Z, Zheng H, Wang X, Han J, Yu N*（于宁波）. An ankle-driven proprioceptive rehabilitation robot during gait: Design, control, and evaluation. IEEE Transactions on Medical Robotics and Bionics, 2026: 1-1. https://doi.org/10.1109/TMRB.2026.3680991 

（3）脑功能重塑机理解析与康复治疗优化

1. Lu, J.#, Cheng, Y.#, Zhang, X., Zhu, Z., Yu, Y., Wang, Y., Wu, J.*, Han, J.*, Yu, N.*(于宁波). Dynamic brain synergy uncovers functional neural coordination in Parkinson's disease under dopaminergic modulation. Journal of NeuroEngineering and Rehabilitation, 2026, 23(82). https://doi.org/10.1186/s12984-026-01891-1 

2. Xinhao Bai, Ge Fang, Hongpeng Wang, Yanding Qin, Jianda Han, Ningbo Yu*(于宁波). Frequency-aware and cross-mamba-enhanced medical image fusion for a real-time surgical navigation framework, Expert Systems with Applications, 2026, https://doi.org/10.1016/j.eswa.2026.132547

3. Lin, J.#, Jin, S.#, You, Y., Liu, J., Lu, J., Shu, Z., Feng, Y., Zhang, Y., Xiao, H., Zhang, Y., Wang. J., Zhao, X., Wang, C.*, Han, J.*, Yu, N.*(于宁波). EEG-fNIRS multilayer brain network analysis revealed functional neural reorganization of rTMS with motor training in stroke. IEEE Transactions on Biomedical Engineering, 2026, 73(1): 269-280. https://doi.org/10.1109/TBME.2025.3580943 

4. Lu, J., Wang, J., Cheng, Y., Shu, Z., Wang, Y., Zhang, X., Zhu, Z., Yu Y., Wu, J., Han, J., Yu, N.*(于宁波). A knowledge-driven framework discovers brain activation-transition- spectrum (ACTS) features for Parkinson's disease. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2024, 32, 3135-3146. https://doi.org/10.1109/TNSRE.2024.3449316 

5. Lu, J.#, Wu, J.#, Shu, Z., Zhang, X., Li, H., Liang, S.*, Han, J. *, Yu, N.*(于宁波). Brain temporal-spectral functional variability reveals neural improvements of DBS treatment for disorders of consciousness. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2024, 32, 923-933. https://doi.org/10.1109/TNSRE.2024.3368434 

6. Lin, J., Lu, J., Shu, Z., Han, J., Yu, N.*(于宁波). Subject-specific modeling of EEG-fNIRS neurovascular coupling by task-related tensor decomposition. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2024, 32, 452-461. https://doi.org/10.1109/TNSRE.2024.3355121 

7. Lu, J.#, Zhang, X.#, Wang, Y., Cheng, Y., Shu, Z., Wang, J., Zhu, Z., Liu, P., Yu, Y., Wu, J.*, Han, J.*, Yu, N.*(于宁波). An fNIRS-based dynamic functional connectivity analysis method to signify functional neurodegeneration of Parkinson's disease. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023, 31, 1199-1207. https://doi.org/10.1109/TNSRE.2023.3242263 

8. Wang, Y.#, Yu, N.#(于宁波), Lu, J., Zhang, X., Wang, J., Shu, Z., Cheng Y., Zhu, Z., Yu, Y., Liu, P., Han, J.*, Wu, J.*. Increased effective connectivity of the left parietal lobe during walking tasks in Parkinson's disease. Journal of Parkinson's Disease, 2023, 13(2), 165-178. https://doi.org/10.3233/JPD-223564 

9. Shu, Z.#, Wu, J.#, Li, H., Liu, J., Lu, J., Lin, J., Liang, S.*, Wu, J.*, Han, J.*, Yu, N.*(于宁波). fNIRS-based functional connectivity signifies recovery in patients with disorders of consciousness after DBS treatment. Clinical Neurophysiology, 2023, 147, 60-68. https://doi.org/10.1016/j.clinph.2022.12.011 

10. 舒智林, 李思宜, 于宁波*, 朱志中, 巫嘉陵, 韩建达. 一种脑肢融合的神经康复训练在线评价与调整方法. 自动化学报, 2022, 48(5): 1209-1219. https://doi.org/10.16383/j.aas.c200452 

专著、报告等 Books & Reports

• Ningbo Yu (于宁波), Christoph Hollnagel, Armin Blickenstorfer, Spyros S. Kollias, Robert Riener, “fMRI-Compatible Robotic Interfaces with Fluidic Actuation”, Robotics: Science and Systems IV, MIT Press, 2009.

• 于宁波，党宇，周静，王翔宇，韩建达.《大模型及具身智能与机器人融合的创新路径与趋势》，南开大学出版社，2026.

• 韩建达，于宁波，卢杰威. 《非侵入式脑机接口智能分析—脑机接口的软能力》，科学出版社（出版中）.