INVITED SPEAKER
Professor Shan Liu,Communication University of China
Speech Title:
Research on Information Propagation Modeling and Control Guidance Strategies in Complex Networks
Abstract:
With the development of internet technology and the popularization of smart devices, media resources and the number of users are constantly increasing. The rapid and frequent dissemination of public opinion information related to emergencies, including false information, increasingly relies on media resource networks and their integration with user social networks. How to utilize the coupling relationship between media resource networks and user social networks to quickly and efficiently disseminate positive information and control the spread of harmful information has significant theoretical value and practical significance. Our researches mainly focus on information dissemination mechanisms, information dissemination models, information dissemination thresholds, and public opinion guidance strategies on multi-layer complex networks, etc. After years of continuous and in-depth research, we have achieved many meaningful research results.
Bio of the Invited Speaker Shan Liu is Professor and Chair of the Department of Intelligent Science at the Communication University of China. She received her Ph.D. degree in Electrical Engineering from Texas A&M University, College Station, Texas, USA, in 2013. She is a committee member of the Chinese Association for Artificial Intelligence, the Chinese Institute of Electronics, the Beijing Society of Image and Graphics, the Association of Fundamental Computing Education in Chinese Universities, the China Automation Society, the National Alliance of Artificial Intelligence and Big Data Innovation Industry in Colleges and Universities, and the Institute of Electrical and Electronics Engineers. She has served as a peer reviewer for a series of IEEE Transactions and other high-level SCI journals. Her current research areas include complex networks, intelligent tags, big data, and artificial intelligence. Prof. Liu has been invited to the University of California, the National Laboratory of the United States, and other countries such as France and Belgium to give lectures and speeches and has gained broad academic influence. She has presided over more than 30 research projects, such as the National Natural Science Foundation of China, the National Social Science Foundation of China, and the National Key Research and Development Program of China, published more than 100 high-level academic papers, and received multiple best paper awards.
Bio of the Invited Speaker Shan Liu is Professor and Chair of the Department of Intelligent Science at the Communication University of China. She received her Ph.D. degree in Electrical Engineering from Texas A&M University, College Station, Texas, USA, in 2013. She is a committee member of the Chinese Association for Artificial Intelligence, the Chinese Institute of Electronics, the Beijing Society of Image and Graphics, the Association of Fundamental Computing Education in Chinese Universities, the China Automation Society, the National Alliance of Artificial Intelligence and Big Data Innovation Industry in Colleges and Universities, and the Institute of Electrical and Electronics Engineers. She has served as a peer reviewer for a series of IEEE Transactions and other high-level SCI journals. Her current research areas include complex networks, intelligent tags, big data, and artificial intelligence. Prof. Liu has been invited to the University of California, the National Laboratory of the United States, and other countries such as France and Belgium to give lectures and speeches and has gained broad academic influence. She has presided over more than 30 research projects, such as the National Natural Science Foundation of China, the National Social Science Foundation of China, and the National Key Research and Development Program of China, published more than 100 high-level academic papers, and received multiple best paper awards.
Professor LeSun, Nanjing University of Information Science and Technology
Speech Title:
Class-driven Graph Attention Network for Multi-label Time Series Classification in Mobile Health
Abstract:
To reduce the complexity of developing an Mobile Health (mHealth) system, methods must be implemented to classify mHealth data effectively and identify the most influential data for predictive outcomes. mHealth data typically manifests as multi-label time series, posing a formidable challenge in accurate classification due to intricate interclass relationships and the complexities of feature extraction. Graph neural networks (GNN) present a promising avenue for capturing class relevance, yet concurrently considering class relevance and temporal features for learning class representations remains a challenging task. Addressing the issue of over-smoothing in embedding learning is crucial in GNN-based class representation. Our research introduces a pioneering architecture termed Class-Driven Graph Attention Networks for multi-label time series classification (C-DGAM). C-DGAM integrates a temporal attention module to derive class representations and employs two function-independent graph attention networks to discern varied relevance between classes.
Bio of the Invited Speaker Dr. Le Sun is a Professor in the School of Computer at Nanjing University of Information Science and Technology, China. She received her PhD degree from Victoria University, Australia in 2016, where she was awarded the Chancellor's citation for the Best PhD Award. In 2018, she was a visiting scholar at Michigan State University. Her primary research areas include XAI, energy-efficient smart healthcare, and data mining. Over the past few years, she has authored more than 50 papers published in prestigious journals and conferences, including IEEE JSAC, IEEE TNNLS, IEEE TCYB, IEEE TITS, IEEE TSC, Info.Sci., and others. Additionally, she has successfully led attended several projects funded by the National Natural Science Foundation of China. She actively contributes to the academic community by serving as a reviewer for many internationally recognized journals and conferences such as PAKDD, ICWS, HISS, and more. She has also been invited to serve as a guest editor and an editorial board member for several SCI journals and EI journals, including IEEE TCE, HISS, EAAI, and Springer Nature. Furthermore, she has applied for and been granted more than 10 Chinese patents. In recognition of her achievements, Dr. Sun has received entrepreneurial support from Shaoxing's "Hometown of Celebrities" Talent Program, as well as the 2022 Nanjing Overseas High-level Talent Double First prize in the competition.
Bio of the Invited Speaker Dr. Le Sun is a Professor in the School of Computer at Nanjing University of Information Science and Technology, China. She received her PhD degree from Victoria University, Australia in 2016, where she was awarded the Chancellor's citation for the Best PhD Award. In 2018, she was a visiting scholar at Michigan State University. Her primary research areas include XAI, energy-efficient smart healthcare, and data mining. Over the past few years, she has authored more than 50 papers published in prestigious journals and conferences, including IEEE JSAC, IEEE TNNLS, IEEE TCYB, IEEE TITS, IEEE TSC, Info.Sci., and others. Additionally, she has successfully led attended several projects funded by the National Natural Science Foundation of China. She actively contributes to the academic community by serving as a reviewer for many internationally recognized journals and conferences such as PAKDD, ICWS, HISS, and more. She has also been invited to serve as a guest editor and an editorial board member for several SCI journals and EI journals, including IEEE TCE, HISS, EAAI, and Springer Nature. Furthermore, she has applied for and been granted more than 10 Chinese patents. In recognition of her achievements, Dr. Sun has received entrepreneurial support from Shaoxing's "Hometown of Celebrities" Talent Program, as well as the 2022 Nanjing Overseas High-level Talent Double First prize in the competition.
Associate Professor Tong-Xing Zheng,Xi’an Jiaotong University
Speech Title:
Reconfigurable Intelligent Surface Empowered Physical Layer Security
Abstract:
6G wireless networks opens a new era of wireless communications from connected things to connected intelligence. The open integration and heterogeneous coexistence of 6G make network security an unprecedented significant and challenging issue. Physical-layer security (PLS), which achieves information secrecy by exploiting the intrinsic characteristics of wireless channels, has been recognized as a powerful approach for safeguarding wireless endogenous security for 6G. However, PLS is highly channel-dependent, which makes the achievable security performance heavily restricted by the quality of wireless channels. This talk will introduce a new PLS paradigm enabled by reconfigurable intelligent surface (RIS). RIS is an emerging metamaterial technology that can reconfigure electromagnetic signal propagation path by adjusting the signal amplitude and phase in a controllable manner, and has the potential to break through PLS bottleneck from channel restricted to channel reconstructed. This report will first introduce the background of PLS, after that the RIS-PLS paradigm will be described accompanying with some of our recent achievements, and finally several open issues will be discussed particularly including how artificial intelligence (AI) can be leveraged.
Bio of the Invited Speaker Tong-Xing Zheng received the B.S. degree in Information Engineering and Ph.D. degree in Information and Communications Engineering from Xi’an Jiaotong University, Xi’an, China, in 2010 and 2016, respectively. From 2017 to 2018, he was a Visiting Scholar with the School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia. He is currently an Associate Professor with Xi’an Jiaotong University. His research interests include B5G/6G emerging wireless technologies, physical layer security, covert communications, reconfigurable intelligent surface, integrated sensing and communications. He has published the book Physical Layer Security in Random Cellular Networks (Springer, 2016), two book chapters, and over 100 papers in telecommunications journals and conference proceedings. He was a recipient of the Excellent Doctoral Dissertation Award of Shaanxi Province in 2019, the First Prize of Science and Technology Award in Higher Institution of Shaanxi Province in 2019 and 2023, the First Prize of Air Force First Aviation Creative Challenge in 2023, and the Best Paper Award at the 2023 International Conference on Ubiquitous Communication. He was honored as an Exemplary Reviewer of IEEE TRANSACTIONS ON COMMUNICATIONS in 2017, 2018, and 2021. He was a Leading Guest Editor of FRONTIERS IN COMMUNICATIONS AND NETWORKS in 2021 and a Guest Editor of WIRELESS COMMUNICATIONS AND MOBILE COMPUTING in 2018. He served as a Session Chair for the IEEE ICC 2022 and IoTCIT 2024. He has served as a TPC member for various IEEE sponsored conferences, including the IEEE GLOBECOM, ICC, WCNC, VTC, and PIMRC.
Bio of the Invited Speaker Tong-Xing Zheng received the B.S. degree in Information Engineering and Ph.D. degree in Information and Communications Engineering from Xi’an Jiaotong University, Xi’an, China, in 2010 and 2016, respectively. From 2017 to 2018, he was a Visiting Scholar with the School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia. He is currently an Associate Professor with Xi’an Jiaotong University. His research interests include B5G/6G emerging wireless technologies, physical layer security, covert communications, reconfigurable intelligent surface, integrated sensing and communications. He has published the book Physical Layer Security in Random Cellular Networks (Springer, 2016), two book chapters, and over 100 papers in telecommunications journals and conference proceedings. He was a recipient of the Excellent Doctoral Dissertation Award of Shaanxi Province in 2019, the First Prize of Science and Technology Award in Higher Institution of Shaanxi Province in 2019 and 2023, the First Prize of Air Force First Aviation Creative Challenge in 2023, and the Best Paper Award at the 2023 International Conference on Ubiquitous Communication. He was honored as an Exemplary Reviewer of IEEE TRANSACTIONS ON COMMUNICATIONS in 2017, 2018, and 2021. He was a Leading Guest Editor of FRONTIERS IN COMMUNICATIONS AND NETWORKS in 2021 and a Guest Editor of WIRELESS COMMUNICATIONS AND MOBILE COMPUTING in 2018. He served as a Session Chair for the IEEE ICC 2022 and IoTCIT 2024. He has served as a TPC member for various IEEE sponsored conferences, including the IEEE GLOBECOM, ICC, WCNC, VTC, and PIMRC.
Professor.QiLiu, South China University of Technology
Speech Title:
Novel View Synthesis and 3D Reconstruction
Abstract:
There is a growing interest in novel view synthesis (NVS) and 3D reconstruction technologies. NVS involves generating new perspectives from existing viewpoints, whereas 3D reconstruction entails creating 3D models of scenes using available views. These technologies are widely used in driverless cars, modern urban development, virtual reality experiences, and the digital restoration of historical buildings. Our group primarily concentrates on various key research areas: (1) Large-scale scene NVS. We have created plug-and-play spatial partitioning and fusion techniques that produce lifelike rendering results for aerial and street scenes, all while greatly cutting down on memory usage. (2) High-precision NVS. We suggested methods for adaptive densification and view-dependent hash encoding to improve the representation of scene lighting and textural details. (3High-precision 3D reconstruction. Our approach simultaneously generates realistic 3D models and novel views. (4) Efficient 3D reconstruction from sparse views. With just 3-6 perspective images, we can quickly create top-notch 3D reconstructions of environments. We are also researching dynamic object reconstruction, underwater scene reconstruction, and object reconstruction using complex materials.
Bio of the Invited Speaker Qi Liu is currently a Professor with the School of Future Technology at South China University of Technology. Dr. Liu received a Ph.D degree in Electrical Engineering from City University of Hong Kong, Hong Kong, China, in 2019. During 2018 - 2019, he was a Visiting Scholar at the University of California Davis, CA, USA. From 2019 to 2022, he worked as a Research Fellow in the Department of Electrical and Computer Engineering, National University of Singapore, Singapore. His research interests include human-object interaction, AIGC, 3D scene reconstruction, and affective computing, etc. Dr. Liu has published over 50 papers in peer-reviewed journals and conferences, including IEEE TFS、TCYB、TCSVT、IoT-J、ACL、CVPR、AAAI, etc., and has been an Associate Editor of the IEEE Systems Journal (2022-), and Digital Signal Processing (2022-). He was also Guest Editor for the IEEE Transactions on Consumer Electronics, IEEE Internet of Things Journal, IET Signal Processing, etc. He was the recipient of the Best Paper Award of IEEE ICSIDP in 2019.
Bio of the Invited Speaker Qi Liu is currently a Professor with the School of Future Technology at South China University of Technology. Dr. Liu received a Ph.D degree in Electrical Engineering from City University of Hong Kong, Hong Kong, China, in 2019. During 2018 - 2019, he was a Visiting Scholar at the University of California Davis, CA, USA. From 2019 to 2022, he worked as a Research Fellow in the Department of Electrical and Computer Engineering, National University of Singapore, Singapore. His research interests include human-object interaction, AIGC, 3D scene reconstruction, and affective computing, etc. Dr. Liu has published over 50 papers in peer-reviewed journals and conferences, including IEEE TFS、TCYB、TCSVT、IoT-J、ACL、CVPR、AAAI, etc., and has been an Associate Editor of the IEEE Systems Journal (2022-), and Digital Signal Processing (2022-). He was also Guest Editor for the IEEE Transactions on Consumer Electronics, IEEE Internet of Things Journal, IET Signal Processing, etc. He was the recipient of the Best Paper Award of IEEE ICSIDP in 2019.