Prof. Youfu Li IEEE Fellow City University of Hong Kong, China |
Biography：Prof. Li received the B.S. and M.S. degrees in electrical engineering from Harbin Institute of Technology China. He obtained the PhD degree from the Robotics Research Group, Dept of Engineering Science of the University of Oxford in 1993. From 1993 to 1995 he was a postdoctoral research staff in the Dept of Computer Science, University of Wales, Aberystwyth, UK. He joined City University of Hong Kong in 1995 and is currently a professor in the Department of Mechanical Engineering. His research interests include robot sensing, robot vision, 3D vision, visual tracking, sensor guided manipulation, mechatronics and automation. In these areas, he has published over 180 papers in SCI listed international journals. Dr Li has received many awards in robot sensing and vision including IEEE Sensors Journal Best Paper Award by IEEE Sensors Council, Second Prize of Natural Science Research Award by the Ministry of Education, 1st Prize of Natural Science Research Award of Hubei Province, 1st Prize of Natural Science Research Award of Zhejiang Province, China. He was on Top 2% of the world’s most highly cited scientists by Stanford University, 2020. He has served as an Associate Editor of IEEE Transactions on Automation Science and Engineering (T-ASE), Associate Editor of IEEE Robotics and Automation Magazine (RAM), Editor of the IEEE Robotics Automation Society's Conference Editorial Board (CEB) and Guest Editor of IEEE Robotics and Automation Magazine (RAM). He is a fellow of IEEE. Title: Visual tracking for robotic applications Abstract: Visual tracking is important for many engineering applications including robotics. Efficient 3D measurement and trajectory tracking presents many challenges. In this talk, I will present our research in 3D visual sensing for trajectory tracking. Different approaches in the 3D visual sensing will be reported. A signature based approach is studied for free form trajectory description in Euclidean space. The signature admits rich invariants due to the computational locality. By implementing the approximate signature, the noise-sensitive high order derivatives are avoided. The trajectory can then be recognized based on the customized signatures similarity metric. To overcome the limitations of traditional cameras in their low dynamic range, high power consumption, and a tendency to motion blurs, a biologically inspired vision is introduced that works asynchronously on pixel levels rather than trapping in frame-rate limitations. This gives rise to a new type of dynamic vision system with its low power consumption, high temporal resolution, and high dynamic range. Some illustrative examples will be presented to show the relevant issues for robotic applications. |
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Prof. Adrian David Cheok IEEE Senior Member Nanjing University of Information Science and Technology, China |
Biography：Adrian David Cheok AM FIET FIEAust FRSA is Full Professor at Nanjing University of Information Science and Technology, Director of the Imagineering Institute, Malaysia, Visiting Professor at Raffles University, Malaysia, Visiting Professor at University of Novi Sad-Serbia, on Technical faculty “Mihailo Pupin”, Serbia, Faculty of Ducere Business School, and CEO of Nikola Tesla Technologies Corporation. In 2024, Professor Adrian David Cheok was honored with induction as a Full Member into Sigma Xi USA, The Scientific Research Honor Society, a recognition that not only signifies his dedication to scientific excellence but also aligns his contributions with those of groundbreaking researchers. Sigma Xi is a beacon of distinction within the global scientific community, boasting over 200 Nobel Laureates among its members, including luminaries such as Albert Einstein. This prestigious society is renowned for its commitment to the advancement of science and engineering and includes among its distinguished members other eminent personalities like Linus Pauling and Guglielmo Marconi, whose pioneering work has indelibly shaped the landscape of modern science and innovation. Professor Cheok’s association with Sigma Xi marks a pinnacle in his career, affirming his commitment to the ethos of rigorous and impactful scientific inquiry. He has been working on research covering mixed reality, human-computer interfaces, wearable computers and ubiquitous computing, fuzzy systems, embedded systems, power electronics. Title: Everywhere Everysense Communication Abstract: This talk outlines new facilities that are arising in the hyperconnected internet era within human media spaces. This allows new embodied interaction between humans, species, and computation both socially and physically, with the aim of novel interactive communication and entertainment. Humans can develop new types of communication environments using all the senses, including touch, taste, and smell, which can increase support for multi-person multi-modal interaction and remote presence. In this talk, we present an alternative ubiquitous computing environment and space based on an integrated design of real and virtual worlds. We discuss some different research prototype systems for interactive communication, culture, and play. |
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Prof. Zheng Yan IEEE Fellow, IET Fellow, AAIA Fellow, AIIA Fellow Xidian University, China |
| Biography：Yan Zheng is a female professor at Xidian University, where she serves as a leading "Huashan Scholar," doctoral supervisor, and Fellow of IEEE, IET, AAIA, and AIIA. She was also named an Academy Fellow by the Finnish Academy of Science in 2017, has been recognized as a top 2% global scientist since 2019, and has been a highly cited scholar in China by Elsevier since 2020. She holds a Bachelor's degree in Information Science and Engineering from Xi'an Jiaotong University, a Master's degree in Computer Organization and Architecture from the same university, and a Master's degree in Information Security from the National University of Singapore. She has been a professor at Xidian University since July 2011. She has long been dedicated to research in trust management, blockchain, information and network security, privacy protection, and data analysis. Over the past decade, she has led or participated in more than 30 projects, including key R&D projects from the Ministry of Science and Technology, National Natural Science Foundation projects, and international cooperation initiatives. She has innovatively proposed a trust management mechanism that adapts to dynamic trust changes while ensuring autonomy and privacy protection. She has also developed a series of security and privacy technologies controlled by trust, which have been widely applied in next-generation wireless communication networks, ubiquitous social networks, cloud computing, IoT, and embedded software. Her work on decentralized trust management supported by blockchain has addressed the challenge of trust management in environments lacking trusted nodes. Title: Trust and Security in Intelligent Mechanics and Human-Computer Interaction: Innovative Solutions Empowered by Blockchain Abstract: With the rapid development of intelligent mechanics and human-computer interaction (HCI) technologies, trust management and cybersecurity have become critical factors in ensuring system reliability and user experience. This presentation will explore how to build efficient trust mechanisms and security frameworks in the context of intelligent mechanics and HCI. We will introduce a blockchain-based decentralized trust management approach that can dynamically adapt to trust changes and provide robust privacy protection. By combining the immutability of blockchain with the automation of smart contracts, we have developed a series of innovative security technologies to address potential privacy breaches and trust issues in intelligent systems. These technologies have been validated across multiple domains and offer new perspectives for the future development of intelligent mechanics and HCI. The presentation will also share our research experiences and outcomes from international cooperation projects, and look ahead to the potential applications of blockchain in intelligent systems. |
