Prof. Jiawen Kang

Guangdong University of Technology

Bio:

Jiawen Kang is a Full Professor at Guangdong University of Technology.  He has published more than 150 research papers in leading journals  and flagship conferences including 12 ESI highly cited papers and 3 ESI hot papers. He is the co-inventor of 16 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), IEEE Computer Society Smart Computing Special Technical Community Early-Career Award，and 12 best paper awards of international conferences (i.e., IEEE WCNC, IEEE IWCMC, IEEE Blockchain, IEEE CPSCom, AAAI Workshop, WWW Workshop, EAI 6GN, ACM DroneCom, IEEE CSCloud, EAI Qshine  and IEEE Scalcom) as well. He is listed in the World's Top 2% of Scientists identified by Stanford University. He is now serving as the editor or guest editor for 11 leading journals including IEEE Journal on Selected Areas in Communications, IEEE Transactions on Vehicular Technology, IEEE Transactions on Network Science and Engineering, IEEE Systems Journal, Frontiers of Computer Science, IET Communications, Transactions on Emerging Telecommunications Technologies and IEEE Networking Letter,  and has also severed as the Co-chair of  ICDCS, IEEE WCNC, IEEE ICC,  IEEE Globecom, IEEE EUC, IEEE things, IEEE HPCC, WCSP, etc. He received  IEEE Outstanding Leadership Award for 2022 EUC Conference (Program Chair) He is a vice-chair of IEEE Technical Committee on Cognitive Networks Special Interest Group on "Wireless Blockchain Networks.

Speech Title: 

Blockchain-Empowered Federated Learning for Healthcare Metaverses

Abstract: 

Given the revolutionary role of metaverses, healthcare metaverses are emerging as a transformative force, creating intelligent healthcare systems that offer immersive and personalized services. The healthcare metaverses allow for effective decision-making and data analytics for users. However, there still exist critical challenges in building healthcare metaverses, such as the risk of sensitive data leakage and issues with sensing data security and freshness, as well as concerns around incentivizing data sharing. In this talk, we first present a user-centric privacy-preserving framework based on decentralized Federated Learning (FL) for healthcare metaverses. To further improve the privacy protection of healthcare metaverses, a cross-chain empowered FL framework is utilized to enhance sensing data security. This framework utilizes a hierarchical cross-chain architecture with a main chain and multiple subchains to perform decentralized, privacy-preserving, and secure data training in both virtual and physical spaces. Moreover, we utilize Age of Information (AoI) as an effective data-freshness metric and propose an AoI-based contract theory model under Prospect Theory (PT) to motivate sensing data sharing in a user-centric manner.

Prof. Wanyang Dai

Nanjing University

Bio: 

Wanyang Dai is a Distinguished Professor in Nanjing University, Chief Scientist in Su Xia Control Technology. He is the current President & CEO of U.S. based (Blockchain & Quantum-Computing) SIR Forum, President of Jiangsu Probability & Statistical Society, Chairman of Jiangsu BigData-Blockchain and Smart Information Special Committee. He received his Ph.D. in mathematics and systems & industrial engineering from Georgia Institute of Technology in USA. He was an MTS and principal investigator in U.S. based AT&T Bell Labs (currently Nokia Bell Labs) with some project won “Technology Transfer” now called cloud system. He was the Chief Scientist in DepthsData Digital Economic Research Institute. He published numerous influential papers in big name journals including Quantum Information Processing, Operations Research, Operational Research, Queueing Systems, Computers & Mathematics with Applications, Communications in Mathematical Sciences, and Journal of Computational and Applied Mathematics. He received various academic awards and has presented over 50 keynote/plenary speeches in IEEE/ACM, big data and cloud computing, quantum computing and communication technology, computational and applied mathematics, biomedical engineering, mathematics & statistics, and other international conferences. He has been serving as IEEE/ACM conference chairs, editors-in-chief and editorial board members for various international journals ranging from artificial intelligence, machine learning, data science, wireless communication, pure mathematics & statistics to their applications.

Speech Title: 

Empowering blockchained federated learning and big model with quantum computing

Abstract: 

To increase the computing power in big model, metaverse, and future internet with blockchained federated learning, we study quantum entanglements and performance modelling for quantum computers through deriving a general spherical coordinate formula for a quantum state of n-qubit register. The associated angle-based n-qubit operation rules on a (n+1)-manifold are established to help developing (e.g., cold atom based) quantum computers, which are simple and efficient in the sense that they reduce the complicated quantum multiplication and division operations to simple addition and subtraction operations just like those used in a conventional computer. The rules for n-qubit operations are realized through measurement-filtering based feedback controls and quantum entanglements with the aim to develop scalable quantum computer chips, where the dynamics of quantum states is governed by a system of stochastic Schrödinger’s equations. The performance models are also derived through the scaling limits (called reflecting Gaussian random fields on a manifold) for n-qubit quantum computer-based quantum storage systems. Examples and simulations will also be provided.

Prof. Hongbing Cheng

Zhejiang University of Technology

Bio:

Hongbing Cheng (Member IEEE) is a Professor of School of Computer Science, Zhejiang University of Technology; he received the Ph.D. degree from the Nanjing University of Posts and Telecommunications and completed post-doctoral research in the State Key Laboratory of New Software Technology of Nanjing University. He has published more than 100 technical papers at different venues, such as IEEE ToN, TFS, TSC, TIFS, TNSM, and ICDCS, ICC. Prof. Cheng served as invited editor of several international journals in some international conferences; and has been invited to give keynote speeches and chair committees, reviewed papers for many international journals and conferences. His research interests include blockchain, cryptography, privacy preserving and information security, computer communications and cloud computing security.

Speech Title: 

Blockchain: From Theory to Application

Abstract: 

Blockchain is a chained data structure consisting of blocks linked in chronological order. Each block needs to maintain an identical, continuously growing, and immutable ledger backup locally; blockchain is a technology that enables the secure sharing of information. Data, obviously, is stored in a database. Transactions are recorded in an account book called a ledger. In this report, we will explain blockchain technology and preliminarily explore its potential application areas. 

Assoc. Prof. Minyue Jin

Chongqing University

Bio

Dr. Minyue Jin received her Ph.D. from University of Science and Technology of China, and had been a visiting postdoc at University of California, San Diego. In 2018, she joined Chongqing University under the “One-hundred Talents Program”. Her research interests include sustainable operations and supply chain management, consumer behavior and marketing strategies. Jin has been published in numerous journals, including Manufacturing & Service Operations Management (UTD 24), European Journal of Operational Research, Omega, International Journal of Production Research, and International Journal of Production Economics.

Speech Title: 

Implications of Coproduction Technology on Waste Management: Who Can Benefit from the Coproduct Made of Leftover Materials?

Abstract: 

In recent years, coproduction technology has been developed and adopted by many third-party coproduct manufacturers (CMs). Coproducts made of leftover materials from traditional manufacturing are strongly attractive to green consumers who are willing to pay a price premium for environmental protection. However, original equipment manufacturers (OEMs) might hesitate to adopt coproduction technology because the coproduct cannibalizes the sales of their traditional products. In this paper, we develop a game-theoretical model to investigate the economic and environmental implications of coproduction that can be leveraged by one OEM or one CM. We find that, from the OEM’s perspective, the dominant strategy can be OEM coproduction, CM coproduction, or No coproduction, which is contingent on the demand from green consumers and the supply of raw materials. We also find that the size of green consumers and the unit cost of raw materials have non-monotone impacts on the CM’s profit. Interestingly, an enlarging size of green consumers might hurt the CM, while an increasing cost of raw materials might benefit the CM. Although coproduction recovers the value of leftover materials, the adoption of coproduction technology increases the total material consumption and the total material waste when the unit cost of raw materials is sufficiently high, making the environment worse off.