Dr. Yao Guo received his B.S. degree in automation and M.S. degree in communication and information system from Sun Yat-sen University, Guangzhou, China in 2011 and 2014, respectively. He earned his Ph.D. degree in robotic vision from the City University of Hong Kong, Hong Kong in 2018. His postdoctoral training was at the Hamlyn Centre for Robotic Surgery, Imperial College London, London, UK from 2018 to 2020.
 Yao Guo, Weidong Chen, Jie Zhao, and Guang-Zhong Yang*, "Medical Robotics: Opportunities in China", Annual Review of Control, Robotics, and Autonomous Systems (ARCRAS), vol. 5, no. 1, pp. 361-383, 2022.
 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), vol. 7, no. 2, pp. 666-673, 2022. (*Co-corresponding author)
 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, https://doi.org/10.1109/THMS.2021.3107519
 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, https://doi.org/10.1109/JBHI.2021.3107532
 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), 2021, vol. 25, no. 10, pp. 4017-4028.
 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)
 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
 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
 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
 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
 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)
 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
 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
 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
 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.
 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)
 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
 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.