Prof. Pingyi Fan Tsinghua University, China Short Bio: Dr. Pingyi Fan is a professor of the Department of Electronic Engineering of Tsinghua University. He received Ph.D. degree at the Department of Electronic Engineering of Tsinghua University in 1994. From 1997 to 1999, he visited the Hong Kong University of Science and Technology and the University of Delaware in the United States. He also visited many universities and research institutes in the United States, Europe, Japan, Hong Kong and Singapore. He has obtained many research grants, including national 973 Project, 863 Project, mobile special project and the key R&D program, national natural funds and international cooperation projects. He has published more than 190 SCI papers (more than 130 IEEE journals), and 4 academic books. He also applied for more than 30 national invention patents, 5 international patents and. He won seven best paper awards of international conferences, including IEEE ICC2020 and Globecom 2014, and received the best paper award of IEEE TAOS Technical Committee in 2020, the excellent editor award of IEEE TWC (2009), etc. He has served as the editorial board member of several Journals, including IEEE and MDPI. He is currently the editorial board member of Open Journal of Mathematical Sciences, the deputy director of China Information Theory society, the co-chair of China's 6G-ANA TG4, and the chairman of Network and Communication Technology Committee of IEEE ChinaSIP. His current research interests are in 6G wireless communication network and machine learning, semantic information theory and generalized information theory, big data processing theory, intelligent network and system detection, etc. Speech Title: Timeliness Challenges for 6G wireless Networks Toward Metaverse Abstract: Although Metaverse is just a concept, it really bring more imagination in the industries and academics. At the same time, 6G wireless networks is also proposed, which bring some new features, especially AI computation and inference. In this case, one can easily think to combine these two hot points into one and find some new things in the world, to change our daily life and promote the happiness index. In this talk, we mainly focus on the implementation timeliness. If the promising scenarios is coming, what techniques we need to prepare in 6G wireless networks. We first introduce the Meatverse concept and its potential applications in our daily life and then present its challenge requirements for communication technologies, especially, on the implementation timeliness. Later on, we analyse the existing status for wireless networks from multiple layers and point out the possible solutions to the existing problems and their corresponding new research directions. Finally, we give a short summary to show what we need to do in next step. | ![]() |
Prof. Jinming Wen Jinan University, China Short Bio: Jinming Wen received the bachelor’s degree in information and computing science from the Jilin Institute of Chemical Technology, Jilin, China, in 2008, the M.Sc. degree in pure mathematics from Mathematics Institute, Jilin University, Jilin, China, in 2010, and the Ph.D degree in applied mathematics from McGill University, Montreal, QC, Canada, in 2015. He is currently a Professor with the College of Information Science and Technology and the College of Cyber Security, Jinan University, Guangzhou, China. He was a Postdoctoral Research Fellow with the Laboratoire LIP from March 2015 to August 2016, University of Alberta, Edmonton, AB, Canada, from September 2016 to August 2017, and University of Toronto, Toronto, ON, Canada, from September 2017 to August 2018. Since September 2018, he has been a Full Professor with Jinan University, Guangzhou, China. He has authored or coauthored more than 50 papers in top journals, including the Applied and Computational Harmonic Analysis, IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, and IEEE Transactions on Wireless Communications, and conferences. His research interests include lattice reduction and sparse recovery. Speech Title: Binary Sparse Signal Recovery with Binary Matching Pursuit Abstract: In numerous applications from communications and signal processing, we often need to acquire a $K$-sparse binary signal from sparse noisy linear measurements. In this talk, we first develop an algorithm called Binary Matching Pursuit (BMP) to recover the $K$-sparse binary signal. According to whether the residual vector is explicitly formed or not at each iteration, we develop two implementations of BMP which are respectively called explicit BMP and implicit BMP. We then analyze their complexities and show that, compared to the Batch-OMP, which is the fastest implementation of OMP, the improvements of the explicit and implicit BMP}algorithms are respectively $n/(2K)$ and $K$ times when some quantities are pre-computed. Finally, we provide sharp sufficient conditions of stable recovery of the support of the sparse signal using mutual coherence and restricted isometry property of the sensing matrix. | ![]() |
![]() | Assoc. Prof. Xin Yan Wuhan University of Technology, China Short Bio: Xin Yan obtained “3551 Optic Valley Talent Plan” of Wuhan city in 2015 and “Science & Technology Prize” of Hubei province in 2016, respectively. He is/was the leaders of several research projects funded by NSFC, Ministry of Education and Hubei Province, respectively. He is the author of three books: Quality of Service and Multicast Routing on Internet (in Chinese) (Science Press), Watermarking (Intech Press) and Advanced Computer Networks (in Chinese) (XuetangX Online). He has 53 high-level research articles on international journals/conferences (such as IEEE Transactions on Computational Social Systems, IEEE Network Magazine, Computer Networks, Ad Hoc Networks, Enterprise Information Systems, Journal of Network and Computer Applications, Ad Hoc & Sensor Wireless Networks, Wireless Communications and Mobile Computing, Physica A and Computer Communications), and 10 patents. He also served as TPC members of international conferences, such as IWWCN2016, CSA2016, CSA2018, ICNISC2018 and ICNISC2019. Speech Title: Real-time estimation of global states on software-defined random opportunistic networks Abstract: This talk proposes a new idea to apply the thoughts of software-defined networks into random opportunistic networks. To realize the software-defined random opportunistic networks gives rise to a critical issue how a controller node to capture the knowledge of real-time global network states. Nevertheless, the existing algorithms that estimate the global states of ad hoc networks are unable to cognize and dynamically compute the real-time global states, being with overloaded messages, in spite of their relatively lower computational complexity normally. To solve this problem, this talk proposes a novel idea to replace message exchanges between nodes by computing the structural properties of networks, with the theory of network eigen-spectral reconstruction to estimate the real-time global states of random opportunistic networks. Some research topics got involved such as eigenvalue filtering are also investigated. The research results expand the theories of network reconstruction and distributed estimation convergence etc., break through the technical bottleneck of real-time computation for dynamic global state information, clear the critical technical obstacles for the implementation of software-defined network thoughts, and break a new path to implement both green and secure communications. |