Dr. Xiaochun Cheng
Middlesex University, London, UK

Xiaochun Cheng received the BEng Degree in Computer Engineering in 1992, PhD in Computer Science in 1996. He visited Queen’s University of Belfast between 1997 and 1998. He was a Postdoc Research Associate at Sheffield University between 1998 and 2000. He was a Lecturer in Reading University between 2000 and 2005. He has been a Senior Lecturer since 2006 and since 2012 the Computer Science Project Coordinator in Middlesex University. One project was funded with 16 Million Euro budget. He is a member of the IEEE SMC Technical Committee on Computational Intelligence, IEEE SMC Technical Committee on Intelligent Internet Systems, IEEE Communications Society Communications and Information Security Technical Committee, IEEE Technical Committee on Cloud Computing, BCS AI Specialist Group, BCS Information Security Specialist Group. He has been Outstanding Ph.D. Thesis Award Chair of IEEE Technical Committee on Cloud Computing. He contributed for five times best conference paper awards so far. 3 his papers are in the 2020 top 1% of the academic field by Data from Essential Science Indicators. He won 3 times national competitions. He won National Science and Technology Advance Award.

Artificial Intelligence Computing Solutions and Applications

Artificial Intelligence (AI) has been applied to more and more applications. Xiaochun Cheng researched both symbolic and numeric AI computing solutions and applied different AI computing solutions into several projects, including security, e-learning, system engineering, management, communication network,  et al. This speech will review relevant AI computing solutions and AI applications, rational the potential and limitations of relevant AI computing solutions, hence support future more and better AI applications by integrating diverse AI computing solutions.

Prof. Jin Li
School of Computer Science, Guangzhou University, China

Jin Li is currently a professor and vice dean of School of Computer Science, Guangzhou University. He got his Ph.D degree in information security from Sun Yat-sen University at 2007. His research interests include design of secure protocols in Artificial Intelligence, Cloud Computing (secure cloud storage and outsourcing computation) and cryptographic protocols. He has published more than 100 papers in international conferences and journals, including IEEE INFOCOM, IEEE TIFS, IEEE TPDS, IEEE TOC and ESORICS etc. His work has been cited more than 11000 times at Google Scholar and the H-Index is 40. He is Editor-in-Chief of International Journal of Intelligent Systems. He also serves as Associate editor for several international journals, including IEEE Transactions on Dependable and Secure Computing, Information Sciences.

Blockchain-based Secure Data Sharing Platform in IoT

With the rapid development of IoT techniques, IoT networks constantly generate a large amount of data which contain valuable information for various industrial applications after collecting and analyzing. However, it is almost impossible to enable users to effectively contribute their data without privacy guarantees and incentive mechanisms. Such challenges seriously restrict the data sharing in IoT networks. To this end, based on the blockchain platform, we propose a data incentive mechanism to provide data privacy and fairness measures for users in IoT. Moreover, we give two different constructions of the proposed mechanism and analyze their performances on privacy protection and transaction efficiency.