Educational Background：

• 2013 - 2016 University of Paris-Est, Ph.D., Signal, Image, Automatic
• 2009 - 2012 Huazhong University of Science and Technology, M.S., Control Theory and Control Engineering
• 2005 - 2009 Wuhan University of Technology, B.S., Measurement and Control Technology and Instrumentation

Work Experience：

• 2025 – Present:  Shenzhen Loop Area Institute, Professor
• 2025 – Present: Shenzhen Research Institute，Nankai University , Professor
• 2023 – Present: College of Artificial Intelligence, Nankai University, Professor
• 2022 – 2025:  Department of Mechanical Engineering, Imperial College London，Honorary Lecturer
• 2021 – 2023:  College of Artificial Intelligence, Nankai University, Associate Professor
• 2019 – 2021:  Department of Mechanical Engineering, Imperial College London，Research Associate
• 2017 – 2018:  University of Paris-Est Créteil, LISSI Lab, Postdoctoral Researcher
• 2016 – 2017: University of Paris-Est Créteil, IUT, ATER

Huo Weiguang, PhD, is a Professor and Doctoral Supervisor at the School of Artificial Intelligence, Nankai University, and a Professor at Shenzhen Loop Area Institute (SLAI). He received the title of Honorary Lecturer from Imperial College London, UK. He earned his PhD from the University of Paris-Est, France, and completed postdoctoral research at Imperial College London. His research interests include wearable robotics, functional electrical stimulation, and intelligent diagnostic and treatment technologies. He has published more than 50 academic papers, several of which have appeared in leading journals such as npj Digital Medicine, IEEE TRO, IEEE JBHI, and IEEE TNSRE. He has led multiple national and provincial-level projects, including those funded by the National Key Research and Development Program and the National Natural Science Foundation of China. He developed intelligent diagnostic technology for Parkinson's disease that has undergone preliminary clinical application. This technology has been featured in a BBC special report and covered by CCTV's "China News" and "Morning News" programs. Cooperation in AI automation, and robotics fields and applications from outstanding students are welcome.

Representative Publications (past 5-10 years, in order of impact)：

[1] J. Han, Z. Tian, J. Wu, K. Zhang, S. Li, F. Baig, P. Liu, R. Vaidyanathan, F. Morgante, W. Huo* ,“Deep learning-enabled Accurate Assessment of Gait Impairments in Parkinson’s Disease Using Smartphone Videos”, npj Digital Medicine, vol. 9, no. 98, 2026.

[2] Y. Zhao, S. Li, J. Han, W. Huo*, “Robust Adaptive Neural Force Control of a SEA-Based Knee Exoskeleton with Low Impedance”, IEEE/ASME Transactions on Mechatronics, vol.30, no.6, pp. 5352 - 5363, 2025.

[3] Z. Liu, W. Huo*, Z. Yu, P. Bentley, A. Bull, R. Vaidyanathan*, “Continuous Estimation of FES-induced Neuromuscular Fatigue Using Mechanomyography Signals”, IEEE Journal of Biomedical and Health Informatics, vol.29, no.11, pp. 7969 - 7981, 2025.

[4] Z. Guo, Z. Wang, Y. Wang, W. Huo*, J. Han, “Continuous Estimation of Swallowing Motion with EMG and MMG Signals”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.33, pp. 787 - 797, 2025. 

[5] P.Wattanasiri, S. Wilson, W. Huo*, R. Vaidyanathan*, “Gesture Recognition through Mechanomyogram Signals: An Adaptive Framework for Arm Posture Variability”,  IEEE Journal of Biomedical and Health Informatics, vol.29, no. 4, pp. 2453 - 2462, 2025.

[6] S. Zhang, N. Yu, Z. Guo, W. Huo*, J. Han, “Single-Channel sEMG-Based Estimation of Knee Joint Angle Using a Decomposition Algorithm with a State-Space Model”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.31, pp.4703-4712, 2023.

[7] Q. Zeng, P. Liu, N. Yu, J. Wu*, W. Huo*, J. Han*, Video-based quantification of gait impairments in Parkinson’s disease using skeleton-silhouette fusion convolution network”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.31, pp.2912-2922, 2023.

[8] W. Huo*, M. A. Alouane, V. Bonnet, J. Huang, Y. Amirat, R. Vaidyanathan, and S. Mohammed, “Impedance Modulation Control of a Lower Limb Exoskeleton to Assist Sit- to-Stand Movements”, IEEE Transactions on Robotics, vol. 38, no. 2, pp.1230-1249, 2022. 

[9] C. Caulcrick, W. Huo*, E. Franco, S. Mohammed, W. Hoult, R. Vaidyanathan, “Model Predictive Control for Human-Centred Lower Limb Robotic Assistance”, IEEE Transactions on Medical Robotics and Bionics, vol. 3, no. 4, pp.980-991, 2021.

[10] C. Caulcrick, W. Huo*, W. Hoult, R. Vaidyanathan, “Human Joint Torque Modelling with MMG and EMG during Lower Limb Human-Exoskeleton Interaction”, IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 7185 - 7192, 2021.

[11] L. Formstone, W. Huo*, S. Wilson, A. McGregor, P. Bentley, and R. Vaidyanathan, “Quantification of Motor Function Post-stroke using Novel Fusion of Wearable Inertial and Mechanomyographic Sensors”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 29, pp. 1158 - 1167, 2021.

[12] W. Huo*, P. Angeles, Y. Tai, N. Pavese, S. Wilson, M. T. Hu and R. Vaidyanathan, “A Heterogeneous Sensing Suite for Multisymptom Quantification of Parkinson’s Disease”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.  28, no.6, pp.1397 - 1406, 2020.

[13] W. Huo*, M. A. Alouane, Y. Amirat and S. Mohammed, “Force Control of SEA-based Exoskeletons for Multimode Human-Robot Interactions”, IEEE Transactions on Robotics, vol. 36, no. 2, pp. 570-577, 2020.

[14] W. Huo, S. Mohammed*, and Y. Amirat, “Impedance Reduction Control of a Knee Joint Human Exoskeleton System”, IEEE Transactions on Control Systems Technology, vol. 27, no. 6, pp. 2541-2556, 2019.

[15] W. Huo*, V. A. Paniagua, G. Ding, Y. Amirat and S. Mohammed, “Adaptive Proxy-based Controller of an Active Ankle Foot Orthosis to Assist Lower Limb Movements of Paretic Patients”, Robotica, vol. 37, no. 12, pp. 2147-2164, 2019.

[16] W. Huo, S. Mohammed*, Y. Amirat, and K. Kong, “Fast Gait Mode Detection and As- sistive Torque Control of an Exoskeletal Robotic Orthosis for Walking Assistance”, IEEE Transactions on Robotics, vol. 34, no.4, pp. 1035-1052, 2018.

[17] W. Huo*, S. Mohammed, J. C. Moreno, and Y. Amirat, “Lower Limb Wearable Robots for Assistance and Rehabilitation: A State of the Art”, IEEE Systems Journal, vol. 10, no. 3, pp. 1068-1081, 2016. 

[18] Ma, Y. Zhao, X. Lu, C. Wang, J. Han*, Y. Zhang*, W. Huo*, “A Hybrid FES-Soft Exosuit System for Assisting Post-stroke Patients During Walking”, IEEE International Conference on Mechatronics and Machine Vision in Practice (M2VIP), 2024. (最佳会议论文奖)

[19] P. Jung, W. Huo, H. Moon, Y. Amirat, S. Mohammed, “A Novel Gait Phase Detection Algorithm for Foot Drop Correction through Optimal Hybrid FES-Orthosis Assistance”, IEEE International Conference on Robotics and Automation (ICRA), 2021.

[20] W. Huo, V. A. Paniagua, M. Ghedira, Y. Amirat, J. M. Gracies, and S. Mohammed, “Adaptive FES Assistance Using a Novel Gait Phase Detection Approach”, IEEE/RSJ International Conference on Intelligent Robot and Systems (IROS), pp. 5187-5193, 2018.

[21] R. Mallat, V. Bonnet, W. Huo, P. Karasinski, Y. Amirat, M. Khalil, and S. Mohammed, “Human-Exoskeleton System Dynamics Identification Using Affordable Sensors”, IEEE International Conference on Robotics and Automation (ICRA), pp. 6759-6765, 2018.

[22]W. Huo, S Mohammed, Y. Amirat, and K. Kong, “Active Impedance Control of a Lower Limb Exoskeleton to Assist Sit-to-Stand Movement”, IEEE International Conference on Robotics and Automation (ICRA), pp. 3530-3526, 2016.

Books/Monographs：

[1] S. Mohammed, W. Huo H. Rifai, W. Hassani, and Y. Amirat, “Robust Control of an Actuated Orthosis for Lower Limb Movement Restoration”, in Intelligent Assistive Robots- STAR edition, Springer, pp.385-400, 2015.

Patents：

1. 2024: Best Conference Paper Award, IEEE M2VIP Conference

2. 2021: Finalist for Paper Award, IEEE ARM Conference

3. 2018: Finalist for Best Student Paper Award, IEEE ISR Conference