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郭遥

助理教授,博士生导师

通讯地址: 转化医学大楼N220
电子邮件: yao.guo@sjtu.edu.cn

  • 教育背景


    • 2014-2018 香港城市大学,机械与生物医学工程系,博士学位

    • 2011-2014 中山大学,信息科学与技术学院,硕士学位

    • 2007-2011 中山大学,信息科学与技术学院,学士学位

  • 工作经历


    • 2020至今 上海交通大学 生物医学工程学院/医疗机器人研究院,长聘教轨助理教授

    • 2018-2020 Imperial College London, The Hamlyn Centre for Robotic Surgery, Research Associate

    • 2017-2018 香港城市大学 机械与生物医学工程系,Research Assistant

  • 研究方向


    • 人体运动分析,人体姿态估计,人体形状重构,步态分析

    • 脑机接口,精神负荷检测,认知康复与辅助

    • 机器视觉,视觉SLAM,模式识别,机器学习,深度学习

    • 康复机器人, 社交机器人

  • 代表性论文专著

    [21] Chengxi Zhong, Yuyu Jia, David C. Jeong, Yao Guo*, Song Liu*, "AcousNet: A Deep Learning based Approach to Dynamic 3D Holographic Acoustic Field Generation from Phased Transducer Array", IEEE Robotics and Automation Letters (RA-L), 2021,In press, https://doi.org/10.1109/LRA.2021.3130368. (*Co-corresponding author)

    [20] Yao Guo, Weidong Chen, Jie Zhao, and Guang-Zhong Yang*, "Medical Robotics: Opportunities in China", Annual Review of Control, Robotics, and Autonomous Systems (ARCRAS), 2021, To be appeared.

    [19] Yao Guo, Daniel Freer, Fani Deligianni, and Guang-Zhong Yang*, "Eye-tracking for Performance Evaluation and Workload Estimation in Space Telerobotic Training", IEEE Transactions on Human-Machine Systems (THMS), 2021, In press, https://doi.org/10.1109/THMS.2021.3107519

    [18] Xiao Gu, Yao Guo, Guang-Zhong Yang*, and Benny Lo*, "Cross-Domain Self-Supervised Complete Geometric Representation Learning for Real-Scanned Point Cloud Based Pathological Gait Analysis", IEEE Journal of Biomedical and Health Informatics (J-BHI), 2021, In press, https://doi.org/10.1109/JBHI.2021.3107532

    [17] Yao Guo, Xiao Gu, and Guang-Zhong Yang*, "MCDCD: Multi-Source Unsupervised Domain Adaptation for Abnormal Human Gait Detection", IEEE Journal of Biomedical and Health Informatics (J-BHI), vol. 25, no. 10, pp. 4017-4028, 2021, [Paper]


    An overview of the proposed MCDCD framework for abnormal gait recognition.

    t-SNE visualization of the (a) Mocap & (b) EMG feature distributions befor and after unsupervised domain adaptation.

    [16] Frank Po Wen Lo, Yao Guo*, Yingnan Sun, Jianing Qiu, and Benny Ping Lai Lo, "Deep3DRanker: A Novel Framework for Learning to Rank 3D Models with Self-Attention in Robotic Vision", IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 2021. (*Corresponding author) [Paper]

    Flowchart of the proposed Deep3DRanker.

    The model architecture of the proposed Deep3DRanker.

    [15] Yao Guo, Xiao Gu, and Guang-Zhong Yang*, “Human–Robot Interaction for Rehabilitation Robotics.” Digitalization in Healthcare: Implementing Innovation and Artificial Intelligence, Springer, pp. 269-295, 2021. [Chapter]

    Bidirectional HRI in upper-limb prosthetic control, which includes forward prosthetic control and sensory feedback.

    Requirements of HRI for active, natural, and intelligent robot-assisted stroke rehabilitation.

    [14] Xiao Gu, Yao Guo, Fani Deligianni, Guang-Zhong Yang*, “Cross-Subject and Cross-Modal Transfer for Generalized Abnormal Gait Pattern Recognition,” IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 32, no. 2, pp. 546-560, 2020, [Paper]

    Illustration of the cross-subject and cross-modal transfer framework in abnormal gait recognition.

    Illustration of cross-modal cross-subject transfer model.

    [13] Xiao-Yun Zhou*, Yao Guo, Mali Shen, Guang-Zhong Yang, “Application of Artificial Intelligence in surgery,” Frontiers of Medicine, vol. 14, pp. 417-430, 2020, [Paper]

    [12] Xiao Gu, Yao Guo, Fani Deligianni, Guang-Zhong Yang*, “Coupled real-synthetic domain adaptation for real-world deep depth enhancement,” IEEE Transactions on Image Processing (TIP), vol. 29, pp. 6343-6356, 2020, [Paper]


    Overview of the proposed depth enhancement framework..

    Qualitative results of cross-dataset performance on real-world data.

    [11] Yao Guo, Fani Deligianni, Xiao Gu, Guang-Zhong Yang*, “3D Canonical Pose Estimation and Abnormal Gait Recognition with a Single RGB-D Camera,” IEEE Robotics and Automation Letters (RA-L) & IROS 2019, vol. 4, no. 4, pp. 3617-3624, 2019, [Paper]
    centered image
    Overview of the proposed mobile 3D canonical gait analysis system.
    centered image
    Information fusion for human lower limb pose representation and 3D gait analysis in the canonical coordinate system.

    [10] Yao Guo†, Fani Deligianni†, Guang-Zhong Yang*, “From Emotions to Mood Disorders: A Survey on Gait Analysis Methodology,” IEEE Journal of Biomedical and Health Informatics (J-BHI), vol. 23, no. 6, pp. 2302-2316, 2019, (†: equal contribution), [Paper]

    Gait capture systems are mapped in a two-dimensional space from lab-based to home-based environment and from wearable to vision-based.

    Demonstration of four discriminative gait parameters commonly used in emotion detection (neutral, happy, sad, anger and fear).

    [9] Ya-Yen Tsai, Yao Guo, and Guang-Zhong Yang*, “Unsupervised Task Segmentation Approach for Bimanual Surgical Tasks using Spatiotemporal and Variance Properties,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, 2019, pp. 7940-7946.

    [8] Dandan Zhang, Yao Guo, Junhong Chen, Jindong Liu, and Guang-Zhong Yang*, ``A Handheld Master Controller for Robot-Assisted Microsurgery,'' IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, 2019, pp. 394-400.

    [7] Yao Guo, You-Fu Li*, Zhanpeng Shao, “RRV: A spatiotemporal descriptor for rigid body motion recognition,” IEEE Transactions on Cybernetics (TCyber), vol. 48, no. 5, pp. 1513-1525, 2018, [Paper]

    6-D representation of a rigid body motion trajectory.

    Two rigid body motion trajectories m1 and m2 , and the corresponding RRV descriptors S1 and S2 .

    [6] Yao Guo, You-Fu Li*, Zhanpeng Shao, “DSRF: A Flexible Trajectory Descriptor for Articulated Human Action Recognition,” Pattern Recognition, vol. 76, April, pp. 137-148, 2018, [Paper]

    Pipeline of the proposed skeletal representation.

    Illustration of two rigid body configurations. (a) The right arm is modeled as the interconnections of four rigid bodies; (b) The RRB configuration exploits all the reality rigid bodies in the right arm; (c) The VRB configuration uses the discriminative virtual rigid body to represent the movement of the right arm.

    [5] Yao Guo, You-Fu Li*, Zhanpeng Shao, “On multi-scale self-similarities description for effective 3D/6D motion trajectory recognition,” IEEE Transactions on Industrial Informatics (TII), vol. 13, no. 6, pp. 3017-3026, 2017, [Paper]

    Pipeline of the proposed multi-scale similarity matrices.

    Visualization of the MSM representation of the normalized trajectory.

    [4] Yao Guo, You-Fu Li*, and Zhanpeng Shao, “MSM-HOG: A flexible trajectory descriptor for rigid body motion recognition,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017, pp. 4298-4303.

    [3] Yao Guo, You-Fu Li*, and Zhanpeng Shao, “DSRF: A Flexible Descriptor for Effective Rigid Body Motion Trajectory Recognition,” IEEE International Conference on Mechatronics and Automation (ICMA), Harbin, China, 2016, pp. 1673-1678. (Best Conference Paper Award)

    [2] Yao Guo, Kaide Huang, Nanyong Jiang, Xuemei Guo, Guoli Wang*, “An Exponential-Rayleigh model for RSS-based device-free localization and tracking,” IEEE Transactions on Mobile Computing (TMC), vol. 14, no. 3, pp. 484-494, 2015, [Paper]

    The topology of a wireless sensor network for DFLT.

    The multipath components by reflection due to the NLOS target.

    [1] Yao Guo, Kaide Huang, Nanyong Jiang, Xuemei Guo, and Guoli Wang*, “An Exponential-Rayleigh signal strength model for device-free localization and tracking with wireless networks,” International Conference on Intelligent Control and Information Processing (ICICIP), Beijing, China, 2013, pp. 108-113.

  • 教学工作

    2021秋 GE6001 学术写作、规范与伦理

友情链接
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医疗机器人研究院