基本信息

侯增广  研究员、博导、杰青、IEEE Fellow

复杂系统管理与控制国家重点实验室副主任

中国科学院自动化研究所

电子邮件: zengguang.hou@ia.ac.cn

通信地址: 北京市海淀区中关村东路95号

邮政编码: 100190

研究和招生方向

  • 计算智能、智能控制;
  • 机器人与智能系统;
  • 脑机接口与人机交互;
  • 面向运动与认知功能障碍的康复机器人(脑电/肌电信息处理、智能评价、主动控制等)
  • 心脑血管微创介入手术机器人(图像处理、智能导航、智能控制等);
  • 嵌入式系统的软硬件开发。

 招收相关专业的硕士、博士研究生、博士后工作人员。

个人简介

  侯增广,中国科学院自动化研究所研究员,复杂系统管理与控制国家重点实验室副主任,中国科学院脑科学与智能技术卓越创新中心“核心骨干”,中国科学院人工智能创新研究院“2035创新团队”医疗机器人集群负责人、“自主机器智能”方向召集人,是国家杰出青年基金获得者、万人计划入选者、IEEE Fellow。


  分别和瑞士苏黎世联邦理工(ETH)、新西兰奥克兰理工大学(AUT)、英国伯恩茅斯大学(Bournemouth University)等联合承担了国家基金委、科技部、欧盟国际合作项目。和中国康复研究中心、国家康复辅具研究中心、北京协和医院、天坛医院、宣武医院、上海华东医院、华山医院等开展了临床合作研究。


  已发表学术论文100余篇、获得授权发明专利30余项,获国家自然科学二等奖、杨家墀科技奖、中国科学院优秀导师奖、朱李月华优秀教师奖、IEEE神经网络汇刊最佳论文奖(IEEE Trans on Neural Networks Outstanding Paper Award)、亚太神经网络学会(APNNS)杰出贡献奖(Outstanding Achievement Award)等。


指导的研究生多次获得中国科学院院长特别奖、刘永龄奖学金特别奖、国家奖学金、朱李月华奖学金、中国科学院优博论文奖、北京市优博论文奖、CAA优博论文奖、CAAI优博论文奖,以及IFAC大会Travel Grant、WCCI大会Travel Grant、ACC会议Travel Grant等奖项。


工作经历

研究员、博士生导师(2004年始


学术兼职

  • 中国自动化学会副理事长
  • 北京人工智能学会副理事长
  • 智能机器人专业委员会副主任委员
  • 亚太神经网络学会(APNNS)副主席(VP)
  • 国际神经网络学会(INNS)理事(BOG)
  • IFAC机器人技术委员会委员
  • IFAC人机系统技术委员会委员
  • 《IEEE Transactions on Cybernetics》编委
  • 《Neural Networks》编委
  • 《控制理论与应用》编委
  • 《智能科学与技术学报》编委
  • 《机器人》编委

曾担任IEEE神经网络技术委员会主席(Chair, NNTC, IEEE CIS)、 IEEE动态规划与强化学习技术委员会主席(Chair, ADPRLTC,  IEEE CIS),曾担任IEEE计算智能学会(CIS) E-Letter的Editor、期刊《自动化学报》、《IEEE Computational Intelligence Magazine》、《IEEE Transactions on Neural Networks》、《Journal of Intelligent and Fuzzy Systems》、《International Journal of Intelligent Systems Technologies and Applications》、《International Journal of Cognitive Informatics and Natural Intelligence》等编委。


获奖情况

  • 2018,IEEE Fellow

  • 2017,国家自然科学二等奖(第二完成人)

  • 2017,亚太神经网络学会(APNNS)杰出贡献奖(Outstanding Achievement Award) 

  • 2017,CAA优秀博士论文导师奖

  • 2016,国家“万人计划”领军人才

  • 2015,中国科学院“优秀研究生导师奖”

  • 2015,CAA自然科学奖一等奖

  • 2014,政府特殊津贴

  • 2013,IEEE Transactions on Neural Networks Outstanding Paper Award 

  • 2013,朱李月华优秀教师奖

  • 2012,国家杰出青年基金

  • 2010,杨家墀科技奖

发明专利

国际PCT专利(部分)

  • 专利名称:Upper limb rehabilitation robot system,专利授权号:US10596056B2,授权日期:20200324。
  • 专利名称:Multi-Posture Lower Limb Rehabilitation Robot,专利公开号:US20180133088A1,公开日期:20180517。

国家发明专利(部分)

  • 专利名称:基于脑-机接口的注意力调控系统,受理公开号:CN110522447A,公开日期:2019/12/3。
  • 专利名称:基于虚拟现实技术的康复功能评定装置及方法,受理公开号:CN107993720A,公开日期:2018/5/4。
  • 专利名称:软体气驱的手部康复装置,授权公开号:CN107280915B,授权日期:2019/9/24。
  • 专利名称:一种三自由度腕关节康复机器人及其系统,授权公开号:CN106361539B,授权日期:2019/9/24。
  • 专利名称:一种上肢康复机器人手指及手腕训练装置,授权公开号:CN105796285B,授权日期:2017/11/21。
  • 专利名称:一种变阻抗和基于事件的触觉反馈控制方法,授权公开号:CN105824248B,授权日期:2018/9/25。
  • 专利名称:基于阻抗控制的康复训练方法,授权公开号:CN104644378B,授权日期:2017/6/13。
  • 专利名称:任务导向式主动训练控制方法及相应的康复机器人,授权公开号:CN104492066B,授权日期:2017/2/22。
  • 专利名称:截瘫患者用下肢康复医疗机器人”,专利号:CN200910075068.5,授权日期:2011.5.11
  • 专利名称:微创血管介入手术机器人送管机构”,专利号:CN201010221156.4,授权日期:2011.10.12
  • 专利名称:微创血管介入手术机器人送管机构的控制装置,专利号:CN201010221159. 8,授权日期:2012.4.25

部分学术论文

[1]  Wang, C., Peng, L., Hou, Z.G.*, Li, J., Zhang, T., and Zhao, J., “Quantitative assessment of upper-limb motor function for post-stroke rehabilitation based on motor synergy analysis and multi-modality fusion”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 28, no. 4, pp. 943-952, April 2020.

[2]  Sun, T., Peng, L., Cheng, L., Hou, Z.G.*, and Pan, Y., “Composite learning enhanced robot impedance control”, IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 3, pp. 1052-1059, March 2020.

[3]  Zhou, X., Bian, G., Xie, X., Hou, Z.G.*, Li, R., and Zhou, Y., “Qualitative and quantitative assessment of technical skills in percutaneous coronary intervention: In vivo porcine studies,” IEEE Transactions on Biomedical Engineering, vol. 67, no. 2, pp. 353-364, Feb. 2020.

[4]  L. Luo, L. Peng, C. Wang, and Hou, Z.G.*, “A greedy assist-as-needed controller for upper limb rehabilitation”, IEEE Transactions on Neural Networks and Learning Systems, 2019, vol. 30, no. 11, pp. 3433-3443.

[5]  X. Zhou, G. Bian, X. Xie, Hou, Z.G.*, et al, “Analysis of interventionalists’ natural behaviors for recognizing motion patterns of endovascular tools during percutaneous coronary interventions”, IEEE Transactions on Biomedical Circuits and Systems, 2019, vol. 13, no. 2, pp. 330-342.

[6]  C. Cui, G. Bian, Hou, Z.G.*, J. Zhao, G. Su, H. Zhou, et al., "Simultaneous Recognition and Assessment of Post-Stroke Hemiparetic Gait by Fusing Kinematic, Kinetic, and Electrophysiological Data," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 26, pp. 856-864, 2018.

[7]  Cui, C., Bian, G., Hou, Z.G.*, Zhao, J., and Zhou, H., “A multimodal framework based on integration of cortical and muscular activities for decoding human intentions about lower limb motions”, IEEE Transactions on Biomedical Circuits and Systems, August 2017, vol. 11, no. 4, pp. 889-899.

[8]  J. Wang, W. Wang, and Hou, Z.G.*, “Towards improving engagement in neural rehabilitation: attention enhancement based on brain-computer interface and audiovisual feedback”, IEEE Transactions on Cognitive and Developmental Systems, 2019, available online, doi: 10.1109/TCDS.2019.2959055.

[9]  L. Cheng, Y. Liu, Hou, Z.G., et al, “A rapid spiking neural network approach with an application on hand gesture recognition,” IEEE Transactions on Cognitive and Developmental Systems, 2019, available online, doi: 10.1109/TCDS.2019.2918228

[10] Sun, T., Peng, L., Cheng, L., Hou, Z.G.* and Pan, Y., “Stability-guaranteed variable impedance control of robots based on approximate dynamic inversion”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, available online, doi: 10.1109/TSMC.2019.2930582

[11] Z. G. Hou, L. Cheng, and M. Tan, "Multicriteria optimization for coordination of redundant robots using a dual neural network," IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, vol. 40, no. 4, pp. 1075-1087, 2010.(regular paper) 

[12] Z. G. Hou, A. Zou, L. Cheng, and M. Tan, "Adaptive control of an electrically driven nonholonomic mobile robot via backstepping and fuzzy approach," IEEE Transaction on Control Systems Technology, vol. 17, no. 4, pp. 803-815, 2009.(regular paper) 

[13] Z. G. Hou, L. Cheng, and M. Tan, "Decentralized robust adaptive control for the multiagent system consensus problem using neural networks," IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 39, no. 3, pp. 636-647, 2009.(regular paper) 

[14] Z. G. Hou, M. M. Gupta, P. N. Nikiforuk, M. Tan, and L. Cheng, "A recurrent network for hierarchical control of interconnected dynamic systems," IEEE Transactions on Neural Networks, vol. 18, no. 2, pp. 466-481, 2007.(regular paper) 

[15] A. Zou, K. Dev Kumar, Z. G. Hou, and X. Liu, "Finite-time attitude tracking control for spacecraft using terminal sliding mode and Chebyshev neural network," IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, vol. 41, no. 4, pp. 950-963, 2011. (regular paper) 

[16] L. Cheng, Y. Lin, Z. G. Hou, M. Tan, J. Huang, and W. Zhang, "Adaptive tracking control of hybrid machines: a closed-chain five-bar mechanism case," IEEE/ASME Transactions on Mechatronics, vol. 16, no. 6, pp. 1155-1163, 2011.(regular paper) 

[17] L. Cheng, Z. G. Hou, M. Tan, and X. Wang, "Necessary and sufficient conditions for consensus of double-integrator multi-agent systems with measurement noises," IEEE Transactions on Automatic Control, vol. 56, no. 8, pp. 1958- 1963, 2011. 

[18] Z. G. Hou, "A hierarchical optimization neural network for large-scale dynamic systems," Automatica, vol. 37, no. 12, pp. 1931-1940, 2001. (regular paper) 

[19] A. Zou, K. Dev Kumar, and Z. G. Hou, "Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks," IEEE Transactions on Neural Networks, vol. 21, no. 9, pp. 1457-1471, 2010. (regular paper) 

[20] A. Zou, Z. G. Hou, and M. Tan, "Adaptive control of a class of nonlinear pure-feedback systems using fuzzy backstepping approach," IEEE Transactions on Fuzzy Systems, vol. 16, no. 4, pp. 886-897, 2008.(regular paper) 

 


项目情况

作为项目负责人,正在承担国家重点研发计划项目、国家自然科学基金重点与集成项目、国际合作项目(英国BU、瑞士ETH、新西兰AUT等)、北京市自然科学基金重点项目、中国科学院先导专项项目等。