Speakers
Keynote Speaker #1 Prof. Guan Gui
Nanjing University of Posts and Telecommunications
Title: Intelligent Signal Recognition and Spectrum Management Towards Physical-Layer Security
Abstract
The advent of 6G wireless communication heralds a transformative era defined by pervasive sensing and advanced intelligent identification, pivotal for ensuring physical-layer security. This keynote explores the integration of Artificial Intelligence (AI) and Deep Learning (DL) as indispensable tools for addressing the dynamic and intricate challenges of 6G networks. Emphasizing the revolutionary role of AI, we delve into its applications in signal sensing, detection, classification, and Specific Emitter Identification (SEI). By leveraging gradient-based optimization and advanced neural network architectures, we highlight how DL methodologies surpass traditional rule-based systems through data-driven parameter optimization, enhancing accuracy and adaptability. These advancements are critical in overcoming the limitations of conventional model-based approaches, which struggle in the face of complex interference and uncertain channel conditions inherent to 6G environments. Furthermore, we examine the transformative potential of DL in redesigning baseband functionalities, including coding, decoding, and detection processes, offering innovative solutions that enhance the robustness and efficiency of wireless communication systems. This keynote underscores the necessity of integrating intelligent signal sensing and DL technologies to not only bolster physical security but also foster the evolution of a more efficient and intelligent communication ecosystem.
Bio
Guan Gui (Fellow, IEEE) received a Ph.D. degree from the University of Electronic Science and Technology of China, Chengdu, China, in 2012. From 2009 to 2014, he joined Tohoku University as a research assistant and a postdoctoral research fellow, respectively. From 2014 to 2015, he was an Assistant Professor at the Akita Prefectural University, Akita, Japan. Since 2015, he has been a professor at Nanjing University of Posts and Telecommunications, Nanjing, China. His recent research interests include intelligence sensing and recognition, intelligent signal processing, and physical layer security.
Dr. Gui has published over 200 IEEE Journal/Conference papers and won several best paper awards, e.g., ICC 2017, ICC 2014, and VTC 2014-Spring. His contributions to intelligent signal analysis and wireless resource optimization have earned him the title of Fellow of the IEEE, IET, and AAIA. He received the IEEE Communications Society Heinrich Hertz Award in 2021, top 2% scientists of the World by Stanford University in 2021-2023, the Clarivate Analytics Highly Cited Researcher in Cross-Field in 2021-2023, the Highly Cited Chinese Researchers by Elsevier in 2020-2023, the Member and Global Activities Contributions Award in 2018, the Top Editor Award of IEEE Transactions on Vehicular Technology in 2019, the Outstanding Journal Service Award of KSII Transactions on Internet and Information System in 2020, the Exemplary Reviewer Award of IEEE Communications Letters in 2017, the 2012 Japan Society for Promotion of Science (JSPS) Postdoctoral Fellowships for Foreign Researchers, and the 2018 Japan Society for Promotion of Science (JSPS) International Fellowships for Overseas Researchers. He was also selected as the Jiangsu Specially-Appointed Professor in 2016, the Jiangsu High-level Innovation and Entrepreneurial Talent in 2016, and the Jiangsu Six Top Talent in 2018.
Since 2022, he has been a Distinguished Lecturer of the IEEE Vehicular Technology Society. He is serving or served on the editorial boards of several journals, including IEEE Transactions on Vehicular Technology, IEICE Transactions on Communications, Physical Communication, Wireless Networks, IEEE Access, Journal of Circuits Systems and Computers, Security and Communication Networks, IEICE Communications Express, and KSII Transactions on Internet and Information Systems, Journal on Communications. In addition, he served as the IEEE VTS Ad Hoc Committee Member in AI Wireless, General Co-Chair of EAI MOBIMEDIA 2024, General Co-Chair of ICN2024, General Co-Chair of GAIIS 2024, TPC Chair of IoTML 2024, TPC Chair of FAIML 2024, Executive Chair of IEEE ICCT 2023, Workshop Chair of LANTINCOM2023, TPC Chair of PRAI 2022, TPC Chair of ICGIP 2022, Executive Chair of VTC 2021-Fall, Vice Chair of WCNC 2021, TPC Chair of PHM 2021, Symposium Chair of WCSP 2021, General Co-Chair of Mobimedia 2020, TPC Chair of WiMob 2020, Track Chairs of EuCNC 2021 and 2022, VTC 2020 Spring, Award Chair of PIMRC 2019, and TPC member of many IEEE international conferences, including GLOBECOM, ICC, WCNC, PIRMC, VTC, and SPAWC.
Dr. Gui has published over 200 IEEE Journal/Conference papers and won several best paper awards, e.g., ICC 2017, ICC 2014, and VTC 2014-Spring. His contributions to intelligent signal analysis and wireless resource optimization have earned him the title of Fellow of the IEEE, IET, and AAIA. He received the IEEE Communications Society Heinrich Hertz Award in 2021, top 2% scientists of the World by Stanford University in 2021-2023, the Clarivate Analytics Highly Cited Researcher in Cross-Field in 2021-2023, the Highly Cited Chinese Researchers by Elsevier in 2020-2023, the Member and Global Activities Contributions Award in 2018, the Top Editor Award of IEEE Transactions on Vehicular Technology in 2019, the Outstanding Journal Service Award of KSII Transactions on Internet and Information System in 2020, the Exemplary Reviewer Award of IEEE Communications Letters in 2017, the 2012 Japan Society for Promotion of Science (JSPS) Postdoctoral Fellowships for Foreign Researchers, and the 2018 Japan Society for Promotion of Science (JSPS) International Fellowships for Overseas Researchers. He was also selected as the Jiangsu Specially-Appointed Professor in 2016, the Jiangsu High-level Innovation and Entrepreneurial Talent in 2016, and the Jiangsu Six Top Talent in 2018.
Since 2022, he has been a Distinguished Lecturer of the IEEE Vehicular Technology Society. He is serving or served on the editorial boards of several journals, including IEEE Transactions on Vehicular Technology, IEICE Transactions on Communications, Physical Communication, Wireless Networks, IEEE Access, Journal of Circuits Systems and Computers, Security and Communication Networks, IEICE Communications Express, and KSII Transactions on Internet and Information Systems, Journal on Communications. In addition, he served as the IEEE VTS Ad Hoc Committee Member in AI Wireless, General Co-Chair of EAI MOBIMEDIA 2024, General Co-Chair of ICN2024, General Co-Chair of GAIIS 2024, TPC Chair of IoTML 2024, TPC Chair of FAIML 2024, Executive Chair of IEEE ICCT 2023, Workshop Chair of LANTINCOM2023, TPC Chair of PRAI 2022, TPC Chair of ICGIP 2022, Executive Chair of VTC 2021-Fall, Vice Chair of WCNC 2021, TPC Chair of PHM 2021, Symposium Chair of WCSP 2021, General Co-Chair of Mobimedia 2020, TPC Chair of WiMob 2020, Track Chairs of EuCNC 2021 and 2022, VTC 2020 Spring, Award Chair of PIMRC 2019, and TPC member of many IEEE international conferences, including GLOBECOM, ICC, WCNC, PIRMC, VTC, and SPAWC.
Keynote Speaker #2 Prof. Shihua Li
Southeast University
Title: Intelligent Disturbance Rejection Control for Mechatronic Systems
Abstract
For mechatronic systems, nonlinearities, complex internal dynamics, time-varying parameters, external disturbances and complex work tasks make control design a very challenging work. Compared with high gain control and integral control methods, disturbance estimation based control provides a different way to handle disturbance. Disturbance estimation based robust control method can effectively improve the disturbance rejection ability and ensure the robustness of closed-loop system. Some new research developments and results on this topic will be introduced. Specially we will discuss on various advanced modeling, analysis and intelligent disturbance rejection control techniques for mechatronic control systems with considerations of time delay, constraint safety control. Considering the characteristics of mechatronic control system, several kinds of composite control design schemes based on disturbance estimation and compensation are presented with experimental or application verification results.
Bio
Shihua Li received his bachelor, master, Ph.D. degrees all in Automatic Control from Southeast University, Nanjing, China in 1995, 1998 and 2001, respectively. Since 2001, he has been with School of Automation, Southeast University, where he is a Chief Professor, Jiangsu Specially Appointed Professor.
He is the chairman of IEEE IES Nanjing Chapter, Fellow of IEEE, IET, AAIA and CAA. He is also the Director General of Jiangsu Association of Automation. His main research interests include modeling and nonlinear control theory with applications to mechatronic systems. He has published 3 monographs, over 300 international journal and conference papers with 31000+ citations (Google Scholar). He is one of Clarivate Analytics Highly Cited Researchers all over the world in 2017-2023. He is a winner of the 6th Nagamori Award in 2020.
He is the chairman of IEEE IES Nanjing Chapter, Fellow of IEEE, IET, AAIA and CAA. He is also the Director General of Jiangsu Association of Automation. His main research interests include modeling and nonlinear control theory with applications to mechatronic systems. He has published 3 monographs, over 300 international journal and conference papers with 31000+ citations (Google Scholar). He is one of Clarivate Analytics Highly Cited Researchers all over the world in 2017-2023. He is a winner of the 6th Nagamori Award in 2020.
Keynote Speaker #3 Prof. Ruqiang Yan
Xi'an Jiaotong University
Title: Signal Processing Informed Neural Network for Intelligent Fault Diagnosis
Abstract
The conventional process of fault diagnosis involves two main steps: feature extraction and decision-making. However, with the emergence of deep neural networks, a more efficient data-driven approach for feature extraction has become available. Despite their universal approximation capabilities, neural networks present challenges in terms of interpretability and achieving optimal solutions due to their extensive parameter space. To tackle these issues, this talk presents a novel type of neural network called Signal Processing Information Neural Networks (SPINN). By incorporating prior knowledge from signal processing, SPINN represents a promising approach to fault diagnosis by effectively merging the power of deep neural networks with the insights from signal processing, ultimately leading to improved performance and better interpretability.
Bio
Ruqiang Yan is a Full Professor and Director of International Machinery Center at the School of Mechanical Engineering, Xi’an Jiaotong University, China. He is engaged in research on theoretical methods and engineering applications related to intelligent operation and maintenance of high-end equipment. Dr. Yan is a Fellow of IEEE (2022) and ASME (2019). He is the recipient of several prestigious awards including the First Prize for Technological Invention in Shaanxi Province in 2020, the First Prize for Natural Science from the Ministry of Education in 2020, and the 2019 IEEE Instrumentation and Measurement Society Technical Award. He has led the development of one IEEE standard and published over one hundred papers in IEEE and ASME journals, and other publications. Currently, he serves as an IEEE Instrumentation and Measurement Society Distinguished Lecturer and is the Editor-in-Chief of the IEEE Transactions on Instrumentation and Measurement.
Invited Speaker #1 Prof. Ke Feng
South China University of Technology
Title: Intelligent Senile Disease Prevention and Health Monitoring Based on Wireless Sensing
Abstract
To properly solve the problems of health monitoring and disease prevention for the elderly in an aging society, while taking into account both privacy and application convenience, millimeter-wave radars can be installed in hospital wards and nursing homes. Through the reflection signals, wireless sensing can be achieved. Combined with artificial intelligence, the skeletal models of the human body can be extracted and associated with vital signs signals, thereby realizing the synchronous monitoring and recognition of the vital signs and behaviors of multiple people. The electrocardiogram can be reconstructed from the reflection signals and analyzed in depth to detect potential arrhythmia risks. A deep network model can also be constructed to capture the characteristics of falling behaviors and obtain a high-precision classification model to achieve fall detection. The vital signs, electrocardiogram, behavior characteristics and other data obtained through wireless sensing can provide a diagnostic reference for the medical team. This method not only protects privacy but is also convenient and easy to use. It can prevent the elderly from becoming disabled, shorten the length of hospitalization and realize the efficient utilization of medical resources.
Bio
Ke Feng works at South China University of Technology. He is currently a professor in the School of Electronic and Information Engineering. He serves as the Vice Director for the Intelligent Communication Network and Computer Engineering Technology Engineering Center, SCUT. He also serves as an Expert Advisor of the Guangzhou Science and Technology Bureau and Guangdong Science and Technology Department. His research interests include communications and information theory, with special emphasis on future wireless communication and network, wireless sensing，joint sensing and communication, and artificial intelligence technology used in wireless network. He has published more than 100 papers in academic authoritative journals such as IEEE TCOM, IEEE TVT, IEEE CL and Computer Communications, and academic conferences such as IEEE WCNC, IEEE GLOBECOM. Also, he has obtained more than 20 patents.
Invited Speaker #2 Senior Engineer Feng Zhou
Harbin Institute of Technology
Ttile: High Power and Low Loss Fiber Optic Rotary Coupling Technology for Spaceborne Laser Communication Terminals
Abstract
Satellite optical communication is a method of high-speed data transmission between satellites using lasers as information carriers. As the tasks and requirements of satellite optical communication continue to evolve, the demands on the transmission and reception performance of optical systems in satellite optical communication have become increasingly stringent. Traditional satellite optical communication system designs can no longer fully meet the requirements for high-performance laser terminals.
This report introduces several key technologies that address these challenges:
• Low-loss, high-power fiber coupling in space environments: Utilizing a multi-medium rotating light transmission model and radiation-resistant optical fibers.
• Small-angle fiber collimators: Based on long-distance optical simulation and the design of optical element arrays within limited illumination ranges.
• Miniaturized structures: Achieved through compact symmetric mechanical drives and high-precision mechanical compensation structures.
These technologies effectively solve the issues of low loss, high power, and miniaturization in multi-channel fiber rotation coupling devices in space environments, thereby enabling the integration, miniaturization, and lightweight design of the system. The technology has broad applications across land, sea, air, and space domains.
This report introduces several key technologies that address these challenges:
• Low-loss, high-power fiber coupling in space environments: Utilizing a multi-medium rotating light transmission model and radiation-resistant optical fibers.
• Small-angle fiber collimators: Based on long-distance optical simulation and the design of optical element arrays within limited illumination ranges.
• Miniaturized structures: Achieved through compact symmetric mechanical drives and high-precision mechanical compensation structures.
These technologies effectively solve the issues of low loss, high power, and miniaturization in multi-channel fiber rotation coupling devices in space environments, thereby enabling the integration, miniaturization, and lightweight design of the system. The technology has broad applications across land, sea, air, and space domains.
Bio
Feng Zhou, Ph.D. from Harbin Institute of Technology, is the Director of the Marine Information Equipment Engineering Center at the 8th Research Institute of China Electronics Technology Group Corporation (CETC). He is a Senior Engineer with extensive experience in the development and application of optical transmission components and optoelectronic slip ring technologies.
Dr. Zhou has led numerous significant projects, including the development of critical components for major national engineering programs such as Tianzhou, Tiangong, Beidou, the new generation of spacecraft, and the space station. The technology developed under his leadership has reached internationally leading levels.
He has received several prestigious awards, including:
• Third Prize of National Defense Science and Technology Progress Award
• Second Prize of CETC Science and Technology Progress Award
• Anhui Province Excellent Patent Award
• CETC Distinguished Youth Award
• Most Beautiful CETC Person
Dr. Zhou has led numerous significant projects, including the development of critical components for major national engineering programs such as Tianzhou, Tiangong, Beidou, the new generation of spacecraft, and the space station. The technology developed under his leadership has reached internationally leading levels.
He has received several prestigious awards, including:
• Third Prize of National Defense Science and Technology Progress Award
• Second Prize of CETC Science and Technology Progress Award
• Anhui Province Excellent Patent Award
• CETC Distinguished Youth Award
• Most Beautiful CETC Person