IEEE-6th ICCIS 2022: Communication and Information Systems

Keynote Speakers for ICCIS 2022

Prof. Kin K. Leung
IEEE Fellow
Imperial College London, UK

 

Biography: Kin K. Leung received his B.S. degree from the Chinese University of Hong Kong in 1980, and his M.S. and Ph.D. degrees from University of California, Los Angeles, in 1982 and 1985, respectively. He joined AT&T Bell Labs in New Jersey in 1986 and worked at its successor companies until 2004. Since then, he has been the Tanaka Chair Professor in the Electrical and Electronic Engineering (EEE), and Computing Departments at Imperial College in London. He serves as the Head of Communications and Signal Processing Group in the EEE Department at Imperial. His current research focuses on optimization and machine-learning techniques for system design and control of large-scale communication networks and computer infrastructures. He also works on multi-antenna and cross-layer designs for wireless networks.

He received the Distinguished Member of Technical Staff Award from AT&T Bell Labs in 1994, and was a co-recipient of the 1997 Lanchester Prize Honorable Mention Award. He was elected as a Fellow of the IEEE and IET in 2001 and 2021, respectively. He received the Royal Society Wolfson Research Merits Award from 2004 to 2009 and became a member of Academia Europaea in 2012. Jointly with his co-authors, he also received the IEEE ComSoc Leonard G. Abraham Prize (2021) and several best conference paper awards, including at the IEEE PIMRC 2012, ICDCS 2013 and ICC 2019. He serves as a member (2009-11) and the chairman (2012-15) of the IEEE Fellow Evaluation Committee for Communications Society. He was a guest editor for the IEEE JSAC, IEEE Wireless Communications and the MONET journal, and as an editor for the JSAC: Wireless Series, IEEE Transactions on Wireless Communications and IEEE Transactions on Communications. Currently, he chairs the Steering Committee for the IEEE Transactions on Mobile Computing and is an editor for the ACM Computing Survey and International Journal on Sensor Networks.

Speech Title: Optimization by Machine Learning for Communication Networks

Optimization techniques are widely used to allocate and share limited resources to competing demands in communication networks. The speaker will start by showing the well-known Transport Control Protocol (TCP) as a distributed solution to achieve the optimal allocation of network bandwidth. Unfortunately, factors such as multiple grades of service quality, variable transmission power, and tradeoffs between communication and computation often make the optimization problem for resource allocation non-convex. New distributed solution techniques are needed to solve these problems.
As an illustrative example, the speaker will consider in-network data processing in sensor networks where data are aggregated (fused) along the way they are transferred toward the end user. Finding the optimal solution for the distributed processing problem is NP-hard, but for specific settings, the problem can lead to a distributed framework for achieving the optimal tradeoff between communications and computation costs.
As discussed above, gradient-based iterative algorithms are commonly used to solve the optimization problems. Much research focuses on improving the iteration convergence. However, when the system parameters change, it requires a new solution from the iterative methods. The speaker will present a new machine-learning method by using two Coupled Long Short-Term Memory (CLSTM) networks to quickly and robustly produce the optimal or near-optimal solutions to constrained optimization problems over a range of system parameters.

Prof. Xiang Cheng
IEEE Fellow
Peking University, China

 

Biography: Xiang Cheng (S¡¯05-M¡¯10-SM¡¯13-F¡¯22) received the Ph.D. degree jointly from Heriot-Watt University and the University of Edinburgh, Edinburgh, U.K., in 2009. He is currently a Boya Distinguished Professor of Peking University. His general research interests are in areas of channel modeling, wireless communications, and data analytics, subject on which he has published more than 280 journal and conference papers, 9 books, and holds 17 patents.

Prof. Cheng is a recipient of the IEEE Asia Pacific Outstanding Young Researcher Award in 2015, a Distinguished Lecturer of IEEE Vehicular Technology Society, and a Highly Cited Chinese Researcher in 2020. He was a co-recipient of the 2016 IEEE JSAC Best Paper Award: Leonard G. Abraham Prize, and the 2021 IET Communications Best Paper Award: Premium Award. He has also received the Best Paper Awards at IEEE ITST¡¯12, ICCC¡¯13, ITSC¡¯14, ICC¡¯16, ICNC¡¯17, GLOBECOM¡¯18, ICCS¡¯18, and ICC¡¯19. He has served as the symposium lead chair, co-chair, and member of the Technical Program Committee for several international conferences. Prof. Cheng led the establishment of 3 Chinese standards (including 1 industry standard and 2 group standards) and participated in the formulation of 10 3GPP international standards and 2 Chinese industry standards. He is currently a Subject Editor of IET Communications and an Associate Editor of the IEEE Transactions on Wireless Communications, IEEE Transactions on Intelligent Transportation Systems, IEEE Wireless Communications Letters, and the Journal of Communications and Information Networks, and is an IEEE Distinguished Lecturer. In 2021, he was selected into two world scientist lists, including World¡¯s Top 2% Scientists released by Stanford University and Top Computer Science Scientists released by Guide2Research.

Prof. Min Chen
IEEE Fellow
Huazhong University of Science and Technology, China

 

Biography: Min Chen is a full professor in School of Computer Science and Technology at Huazhong University of Science and Technology (HUST) since Feb. 2012. He is the director of Embedded and Pervasive Computing Lab, and the director of Data Engineering Institute at HUST. He is the founding Chair of IEEE Computer Society Special Technical Communities on Big Data. He was an assistant professor in School of Computer Science and Engineering at Seoul National University before he joined HUST. He is the Chair of IEEE Globecom 2022 eHealth Symposium. His Google Scholar Citations reached 33,850+ with an H-index of 88. His top paper was cited 3,770+ times. He was selected as Highly Cited Researcher from 2018 to 2021. He got IEEE Communications Society Fred W. Ellersick Prize in 2017, and the IEEE Jack Neubauer Memorial Award in 2019. His research focuses on cognitive computing, 5G Networks, wearable computing, big data analytics, robotics, machine learning, deep learning, emotion detection, and mobile edge computing, etc. Min Chen is an IEEE Fellow.

Speech Title: Non-Chip Sensing by Intelligent Fabrics

In future network, the provisioning of ultra-low latency, non-intrusive and immersive service experience creates various challenges, among which sensing without disturning human is critical to obtain multi-modal information in long term. This talk introduces the development of various functional fabrics, which have provided new thoughts for generating novel non-chip sensing services for embracing digital intelligent world.

Prof. Anhui Liang
Shandong University of Science and Technology, China

 

Biography: Professor Anhui Liang is the second level professor, Shandong University of Science & Technology, China. He is a national high level talent. He held several positions, e.g. Chief Scientist, FiberHome Technologies; Chief Scientist, WTD; Deputy Director of University Academic Committee, Nanjing University of Posts and Telecommunications, and Tyco Submarine Systems Ltd. in USA etc. He has published more than 100 papers and patents. He has made significant contributions in the fields of optical fiber communications, vision, biological optical AI, quantum mechanics and Chinese meridian, chromosome optical fibers and biological fibers. He is China Overseas Chinese Contribution Award recipient (2014); Yearly Person of ¡°Scientific Chinese¡±(2015). He has made significant contributions in 7 questions which were among 125 questions: exploration and discovery listed by Science journal. His contributions have been well reported in famous national media. His research topics have been interested in by wide audiences, and there are over 247 thousands of audiences in his two scientific lectures in last years.

Speech Title: The Relative Net Energy Uncertainty Is Equal to the Relative Net Non-locality

One of the 125 unsolved key problems listed in Science magazine is: "Are there any deeper principles behind quantum uncertainty and non-locality?" We think we can solve this key problem in principle.
In this talk, we give a quantitative formula to measure the non-locality, and we find that the relative net energy uncertainty is equal to the relative net non-locality.
We shall study the applications of the new equation in quantum communication, quantum computing, and quantum measurement.