Speakers

Prof. Hanxiong Li, City University of Hong Kong, China

IEEE Fellow, H-index: 51

Brief: Hanxiong Li is a Professor at City University of Hong Kong,IEEE Fellow, China Overseas Chinese Federation of Experts (2011-present), Hunan Provincial Experts (2010-present), China's Thousand Talents Programme (2010-2015),Yangtze River Scholar (2006-2009), and a recipient of the Outstanding Young Scientist Award from the National Natural Science Foundation of China (Overseas Young Scientist B) in 2004. He received his PhD from the University of Auckland, New Zealand, in 1997, and his MSc and BSc degrees from Delft University of Technology, the Netherlands, and the National University of Defence Technology, China, in 1991 and 1982, respectively. Since 2000, he has been working as an Assistant Professor in the Department of Mechanical Engineering and Engineering Management at the City University of Hong Kong, progressively promoted to Associate Professor (2002) and Professor (2008). During his career, Professor Luk has held a number of key positions including Senior Process Engineer at ASM Assembly Automation Ltd, Hong Kong and Research Engineer at the University of Auckland, and Project Manager at China International Trust and Investment Corporation. In addition, he has served as an associate editor for many academic journals.

Research areas: intelligent control and learning, process design and control, electronic packaging processes and distributed parameter systems.

Prof. Honghai Liu, Harbin Institute of Technology, Shenzhen, China

Brief: Honghai Liu, Professor of Harbin Institute of Technology (Shenzhen), Member of the European Academy of Sciences, Fellow of the International Institute of Electrical and Electronic Engineers (FIEEE), Fellow of the British Academy of Engineering and Technology (FIET). He has long been engaged in human-machine interaction, intelligent robotics, theory of medical machine-assisted systems and brain disease applications, and has presided over the National Key Research and Development Programme, the National Natural Science Foundation of China and other projects. His research results have achieved a series of internationally influential innovations in the fields of multi-degree-of-freedom dexterous prosthetics, early diagnosis and treatment of autism, and precise diagnosis and treatment of stroke, and have been successfully applied. He has published more than 400 papers in international authoritative journals and conferences, and now serves as co-editor-in-chief of IEEE Trans. Industrial Informatics and editorial board member of IEEE Trans.

Speech title: Multimodal sensing and control for motor-impaired research and applications.

Abstract: The talk first presents the state of the art in multimodal sensing and control for  motor-impaired research with focuses on neuroprosthetics and afterstroke rehabilitation. It then discusses principles of individual sensing modalities, their combination and their pathways to motor cortex during muscle contraction. Next the talk focuses on wearable sonomyography for neuroprosthetic control and corticomuscular coherence based assessment for afterstroke rehabilitation. The talk is concluded with future directions and challenges.

Prof. Xuguang Lan, Xi’an Jiaotong University, China

Brief: Xuguang Lan is a professor, doctoral supervisor, recipient of the National Outstanding Youth Science Foundation, and member of the Disciplinary Review Group of the Academic Degrees Committee of the State Council. He is currently a professor at the School of Artificial Intelligence, Xi'an Jiaotong University, with research interests in computer vision, robot learning, multi-intelligence game and human-robot cohesive collaboration. He is the director of the Special Committee on Inclusive Robotics of the Chinese Society of Automation, the director and deputy secretary-general of the Chinese Society of Cognitive Science, the deputy director of the Special Committee on Cognitive Systems and Information Processing of the Society of Artificial Intelligence, and the deputy director of the Special Committee on Intelligent Unmanned Systems Modelling and Simulation of the Simulation Society. He is also the vice-chairman of the ‘Intelligent Unmanned System Modelling and Simulation’ committee of the Simulation Society. He has published more than 100 papers in renowned journals and conferences in the field of artificial intelligence and robotics, such as IEEE Trans and ICML/CVPR/RSS, etc. He has obtained more than 20 national invention patents, and has published one edited book. He has presided over more than 10 research projects such as the National Natural Science Foundation of China (NSFC), the National Science and Technology Major Project, and the Science and Technology Innovation 2030 Artificial Intelligence Major Project, and the related research results have been applied in aerospace, aviation and other fields. He serves as an editorial board member of IEEE Transactions on Neural Network Learning System and other international journals. He has served as co-programming chair of IEEE CYBER2019 and ICIRA2021, chair of IEEE RCAR2023 and ICIRA2024, and senior member of IEEE.

Speech title: The challenge of embodied intelligence: world modelling and causal reasoning.

Abstract: The report briefly introduces the challenges of embodied intelligence in the physical world, and proposes an autonomous robot operation method based on common sense and visual reasoning in unstructured scenes, which incorporates linguistic macromodels into robot interactions, enabling robots to reason visually in dynamic unstructured scenes and complete autonomous operations. The report also introduces continuous reinforcement learning for embodied intelligence, multi-robot autonomous collaboration methods guided by decision-making macromodel imagery, and the application of related algorithms in the fields of logistics and aviation.

Prof. Hui Zhang, Hunan University, China

Brief: Zhang Hui, Professor, Doctoral Supervisor, Executive Vice Dean of the Robotics Institute of Hunan University, Deputy Director of the National Engineering Research Centre for Robot Visual Perception and Control Technology, and Director and Deputy Secretary General of the Chinese Society of Image Graphics. He has been selected as ‘Changjiang Scholars’ Distinguished Professor by the Ministry of Education, and ‘Ten Thousand People Plan’ Young Top Talents. He is mainly engaged in robot visual inspection, deep learning image recognition, intelligent manufacturing robotics technology and applications.

In recent years, he has presided over more than 20 major projects of Science and Technology Innovation 2030 - ‘New Generation of Artificial Intelligence’, two key projects of the National Natural Science Foundation of China, the key project of JW1XX, the sub-projects of the National Key R&D Programme, and the sub-projects of the National Science and Technology Support Programme, etc. He has been published in IEEE Transactions and other international journals. He has published more than 70 papers in IEEE Repertoire and other domestic and international journals, authorised 42 national invention patents, 5 computer software copyrights, won 1 second prize of national technical invention in 2018, presided over by the 1st completer to win the first prize of Hunan Provincial Scientific and Technological Advancement in 2022, the second prize of Hunan Provincial Scientific and Technological Advancement in 2019, the first prize of the Science and Technology Advancement Award of the China Commercial Federation in 2019, and won the first prize of the Science and Technology Advancement Award of the Chinese Commercial Federation as the main Completer won 15 provincial and ministerial-level scientific and technological progress awards, the special prize of the 13th teaching achievement of Hunan Province in 2022, and the second prize of the national teaching achievement award of higher education (postgraduate students) in 2022.

Speech title: Multimodal Intelligent Perception Technology and Applications of UAVs in Complex Power Scenarios.

Abstract: An intelligent perception technology based on multimodal information fusion is proposed for infrared thermal fault identification, line tree obstacle classification, and tower tilt detection in UAV inspection tasks in complex power scenarios. By combining visible images, infrared images, point clouds and multispectral data, the challenges of environmental complexity, incomplete information and sensor perception limitations are solved, which significantly improves the perception and cognitive ability of UAS in complex environments. The highlights of the report include: 1) Adaptive image alignment and predictive information migration techniques are proposed to solve the spatial alignment problem of multimodal data, accurately locate power equipment and perform temperature interpretation; 2) A tree barrier classification method based on the fusion of point cloud and multispectral data is designed to make full use of the complementarities between different modalities, accurately identify tree species in power corridors, and improve the accuracy and efficiency of inspection tasks; 3) Developed multi-modal information synergistic tower tilt detection and semantic segmentation technology, which enhances the intelligent level of power facility inspection in complex environments. Through multi-source data fusion and intelligent processing, this report demonstrates how multi-modal perception technology can be utilised to enhance the efficiency, accuracy and security of UAV inspection in complex power scenarios to effectively meet national strategic needs.