IEEE Fellow, IET Fellow
Prof.Dusit (Tao) Niyato
Nanyang Technological University (NTU), Singapore
Dusit Niyato (M'09-SM'15-F'17) is a professor in the School of Computer Science and Engineering, at Nanyang Technological University, Singapore. He received B.Eng. from King Mongkuts Institute of Technology Ladkrabang (KMITL), Thailand in 1999 and Ph.D. in Electrical and Computer Engineering from the University of Manitoba, Canada in 2008. His research interests are in the areas of sustainability, edge intelligence, decentralized machine learning, and incentive mechanism design.
|Ttile：To be determined ...|
To be determined ...
Prof. Jiawen Kang
Guangdong University of Technology, School of Automation, China
Jiawen Kang is a Full Professor at Guangdong University of Technology. He was a postdoc at Nanyang Technological University, Singapore from 2018 to 2021. His research interests mainly focus on blockchain, metaverse, edge intelligence, security and privacy protection, etc. He has published around 100 research papers in leading journals and flagship conferences including 10 ESI highly cited papers and 3 ESI hot papers. He is the co-inventor of 15 granted patents and has won IEEE VTS Best Paper Award, IEEE Communications Society CSIM Technical Committee Best Journal Paper Award, IEEE Best Land Transportation Paper Award, IEEE HITC Award for Excellence in Hyper-Intelligence Systems (Early Career Researcher award), and 10 best paper awards of international conferences (e.g., WCNC 2020) as well. He is listed in the World’s Top 2% Scientists identified by Stanford University. He is now serving as the editor or guest editor for many leading journals including IEEE JSAC, TNSE, ISJ, and has also severed as the Co-chair of ICC Workshop, WCNC Workshop, ICDCS Workshop, Globcom 2021 Workshop, and HPCC Workshop, etc. He is a vice-chair of IEEE Technical Committee on Cognitive Networks Special Interest Group on "Wireless Blockchain Networks".
|Ttile：Blockchain-based Federated Learning for Industrial Metaverses|
The emerging industrial metaverses realize the mapping and expanding operations of physical industry into virtual space for significantly upgrading intelligent manufacturing. The industrial metaverses obtain data from various production and operation lines by Industrial Internet of Things (IIoT), and thus conduct effective data analysis and decision-making, thereby enhancing the production efficiency of the physical space, reducing operating costs, and maximizing commercial value. However, there still exist bottlenecks when integrating metaverses into IIoT, such as the privacy leakage of sensitive data with commercial secrets, IIoT sensing data freshness, and incentives for sharing these data. In this talk, we introduce a user-defined privacy-preserving framework to improve privacy protection of industrial metaverse. A cross-chain empowered federated learning framework is further utilized to perform decentralized, secure, and privacy-preserving data training. Moreover, we introduce the age of information as the data freshness metric and thus design an age-based contract model to motivate data sensing among IIoT nodes.
Assoc. Prof. Xiang Li
Tsinghua University, China
Xiang Li is an Associate Professor with the Department of Automation, Tsinghua University. He has been the Associate Editor of IEEE Robotics and Automation Letters since 2022. He was the Associate Editor of IEEE Robotics & Automation Magazine from 2019 to 2021 and the Associate Editor of ICRA from 2019 to 2021. He received the Highly Commended Paper Award in 2013 IFToMM, the Best Paper in Robotic Control in 2017 ICAR, the Best Application Paper Finalists in 2017 IROS, and the T. J. Tarn Best Paper in Robotics in 2018 IEEE ROBIO. His current research interests include robotic manipulation, vision-based control, micro/nano robots, and human-robot interaction.
|Ttile：To be determined ...|
Abstract：To be determined ...