Keynote Speakers of ICCSN2025
Prof. T. Aaron Gulliver
Fellow of the Engineering Institute of Canada
Fellow of the Canadian Academy of Engineering
University of Victoria, Canada
Speech Title: Physical Layer Authentication for
Wireless Applications
Abstract: Internet of things (IoT) devices have become ubiquitous and enable applications such as smart homes, intelligent healthcare, and intelligent transportation. However, deployment costs limit cellular network coverage in remote and rural areas, and the reliability of cellular infrastructure during natural disasters is a concern. Thus, space and ground network integration has been proposed to provide global connectivity and support a wide range of IoT applications. Unfortunately, spoofing attacks are problematic due to network complexity and heterogeneity. Authentication for access control is an efficient way to ensure user legitimacy. However, upper layer authentication (ULA) is challenging due to limited computational power, high complexity, and communication overhead. Thus, physical layer authentication (PLA) has been proposed to aid ULA in solving these problems. PLA exploits the fact that legitimate parties and attackers have distinct physical characteristics that are unique between pairs of connected peers based on their spatial locations.
An adaptive PLA scheme using machine learning (ML) is given for IoT applications in urban environments. A one-class classifier support vector machine (OCC-SVM) is employed using the magnitude and real and imaginary parts of the received signal as features. This provides a high authentication rate (AR). Furthermore, an adaptive PLA scheme is presented for collaboration between distributed IoT devices in multiple-input-multiple-output (MIMO) systems. Two majority voting schemes are presented for practical IoT applications where the devices have limited computing capabilities. A scheme for low earth orbit (LEO) satellites is proposed that employs ML with Doppler frequency shift (DS) and received power (RP) features.
Biography: T. Aaron Gulliver received the Ph.D. degree in electrical engineering from the University of Victoria, Victoria, BC, Canada, in 1989. From 1989 to 1991, he was a Defence Scientist with Defence Research Establishment Ottawa, Ottawa, ON, Canada. He has held academic positions at Carleton University, Ottawa, and the University of Canterbury, Christchurch, New Zealand. He joined the University of Victoria in 1999 and is a Professor with the Department of Electrical and Computer Engineering and the Canada Research Chair in Advanced Wireless Communications. He is a Fellow of the Engineering Institute of Canada and the Canadian Academy of Engineering. He has published over 1000 papers and supervised over 150 graduate students. His research interests include information theory, algebraic coding theory, machine learning, smart grid, intelligent networks, cryptography, and security.
Abstract: Internet of things (IoT) devices have become ubiquitous and enable applications such as smart homes, intelligent healthcare, and intelligent transportation. However, deployment costs limit cellular network coverage in remote and rural areas, and the reliability of cellular infrastructure during natural disasters is a concern. Thus, space and ground network integration has been proposed to provide global connectivity and support a wide range of IoT applications. Unfortunately, spoofing attacks are problematic due to network complexity and heterogeneity. Authentication for access control is an efficient way to ensure user legitimacy. However, upper layer authentication (ULA) is challenging due to limited computational power, high complexity, and communication overhead. Thus, physical layer authentication (PLA) has been proposed to aid ULA in solving these problems. PLA exploits the fact that legitimate parties and attackers have distinct physical characteristics that are unique between pairs of connected peers based on their spatial locations.
An adaptive PLA scheme using machine learning (ML) is given for IoT applications in urban environments. A one-class classifier support vector machine (OCC-SVM) is employed using the magnitude and real and imaginary parts of the received signal as features. This provides a high authentication rate (AR). Furthermore, an adaptive PLA scheme is presented for collaboration between distributed IoT devices in multiple-input-multiple-output (MIMO) systems. Two majority voting schemes are presented for practical IoT applications where the devices have limited computing capabilities. A scheme for low earth orbit (LEO) satellites is proposed that employs ML with Doppler frequency shift (DS) and received power (RP) features.
Biography: T. Aaron Gulliver received the Ph.D. degree in electrical engineering from the University of Victoria, Victoria, BC, Canada, in 1989. From 1989 to 1991, he was a Defence Scientist with Defence Research Establishment Ottawa, Ottawa, ON, Canada. He has held academic positions at Carleton University, Ottawa, and the University of Canterbury, Christchurch, New Zealand. He joined the University of Victoria in 1999 and is a Professor with the Department of Electrical and Computer Engineering and the Canada Research Chair in Advanced Wireless Communications. He is a Fellow of the Engineering Institute of Canada and the Canadian Academy of Engineering. He has published over 1000 papers and supervised over 150 graduate students. His research interests include information theory, algebraic coding theory, machine learning, smart grid, intelligent networks, cryptography, and security.
Prof. Nian Fushun
Chief Scientist of Test Instruments at China Electronics Technology Group Corporation (CETC)
Director of the Key Laboratory of Electronic Testing Technology
Ceyear Technologies Co., Ltd. / The 41st Institute of CETC/ Key
Laboratory of Electronic Testing Technology, China
Speech Title: Development of
Electronic Measurement Technology
Abstract: Facing the measurement needs of electronic information systems such as 5G/6G mobile communications, satellite Internet, high-speed digital communications, digital phased array radar, electronic countermeasures, etc., this paper introduces the development status and trend of measurement instruments such as simulation and measurement evaluation of complex electromagnetic environment, parameter characterization and measurement of high-speed digital transmission network, millimeter wave and THz measurement, antenna and material measurement, analyzes the development trends of cutting-edge measurement technologies such as broadband and high-speed measurement, time domain and frequency domain measurement, steady-state and transient measurement, and proposes measurement and computer, The modern measuring instrument architecture (MC3I), which is deeply integrated with control, communication and artificial intelligence, predicts the future development direction and suggestions.
Biography: Nian Fushun, Chief Scientist of Test Instruments at China Electronics Technology Group Corporation (CETC) and Director of the Key Laboratory of Electronic Testing Technology, has long been engaged in scientific research, development, and management of electronic testing instruments. He led research on the design and manufacturing technology of microwave, millimeter-wave, and terahertz circuits, establishing a product system for active and passive components characterized by wide bandwidth, achieving full domestic production of key components for microwave, millimeter-wave, and terahertz testing instruments. He spearheaded the development of continuous-wave, multi-port, pulse, and nonlinear vector network analyzers, enabling China's microwave, millimeter-wave, and terahertz vector network analyzers to develop systematically and at scale, with testing frequencies covering 10 kHz to 750 GHz. Using vector network analyzers as core instruments, he constructed electromagnetic material, antenna, and radar cross-section testing systems, solving measurement and evaluation challenges for on-chip antennas, low-sidelobe antennas, large phased-array antennas, stealth materials, and stealth targets, thereby expanding the application scope of vector network analyzers.
Abstract: Facing the measurement needs of electronic information systems such as 5G/6G mobile communications, satellite Internet, high-speed digital communications, digital phased array radar, electronic countermeasures, etc., this paper introduces the development status and trend of measurement instruments such as simulation and measurement evaluation of complex electromagnetic environment, parameter characterization and measurement of high-speed digital transmission network, millimeter wave and THz measurement, antenna and material measurement, analyzes the development trends of cutting-edge measurement technologies such as broadband and high-speed measurement, time domain and frequency domain measurement, steady-state and transient measurement, and proposes measurement and computer, The modern measuring instrument architecture (MC3I), which is deeply integrated with control, communication and artificial intelligence, predicts the future development direction and suggestions.
Biography: Nian Fushun, Chief Scientist of Test Instruments at China Electronics Technology Group Corporation (CETC) and Director of the Key Laboratory of Electronic Testing Technology, has long been engaged in scientific research, development, and management of electronic testing instruments. He led research on the design and manufacturing technology of microwave, millimeter-wave, and terahertz circuits, establishing a product system for active and passive components characterized by wide bandwidth, achieving full domestic production of key components for microwave, millimeter-wave, and terahertz testing instruments. He spearheaded the development of continuous-wave, multi-port, pulse, and nonlinear vector network analyzers, enabling China's microwave, millimeter-wave, and terahertz vector network analyzers to develop systematically and at scale, with testing frequencies covering 10 kHz to 750 GHz. Using vector network analyzers as core instruments, he constructed electromagnetic material, antenna, and radar cross-section testing systems, solving measurement and evaluation challenges for on-chip antennas, low-sidelobe antennas, large phased-array antennas, stealth materials, and stealth targets, thereby expanding the application scope of vector network analyzers.
His scientific achievements have earned him one National Science and Technology Progress Award (Second Class), six provincial/ministerial-level Science and Technology Progress Awards (First Class), 60 invention patents, and three national standards. He enjoys the State Council's Special Government Allowance and has been honored with titles such as National Model Worker, Outstanding Individual in the Shenzhou-6 Manned Space Mission, Taishan Scholar Climbing Plan Expert, Shandong Province Outstanding Mid-Career and Young Expert, and Qilu Most Beautiful Scientific and Technological Worker.
Prof. Zhu Han
Fellow of AAAS, Fellow of IEEE
Distinguished Member of the ACM
University of Houston, USA
Speech Title: The Transformative
Impact of Generative AI: Strategies, Applications, and Innovations
Abstract: This speech explores the transformative potential of Generative AI (GAI) across various domains. Firstly, we examine the use of Large Language Models (LLMs) in repeated games to develop practical strategies aligning with the folk theorem's equilibrium conditions, enhancing cooperative behavior through future payoff considerations. Secondly, we address low-light image enhancement in teleoperation using diffusion-based AI-generated content (AIGC) models. A Vision Language Model (VLM)-empowered contract theory framework optimizes AIGC task allocation and pricing under information asymmetry, improving resource management for teleoperators and edge servers. In the realm of autonomous driving, we integrate Federated Learning (FL) with Vision-language models (VLMs) in Graph Visual Question Answering (GVQA), highlighting advancements in privacy preservation, reduced communication costs, and maintained model performance. Lastly, an LLM-based semantic communication (SC) framework for underwater communication is presented, demonstrating efficient data transmission and resilience against noise and signal loss by performing semantic compression and prioritization of image data. These innovations collectively illustrate the broad impact of AI technologies, shaping strategies, and enhancing applications across various fields.
Biography: Zhu Han received the B.S. degree in electronic engineering from Tsinghua University, in 1997, and the M.S. and Ph.D. degrees in electrical and computer engineering from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2002, he was an R&D Engineer of JDSU, Germantown, Maryland. From 2003 to 2006, he was a Research Associate at the University of Maryland. From 2006 to 2008, he was an assistant professor at Boise State University, Idaho. Currently, he is a John and Rebecca Moores Professor in the Electrical and Computer Engineering Department as well as the Computer Science Department at the University of Houston, Texas. Dr. Han is an NSF CAREER award recipient of 2010, and the winner of the 2021 IEEE Kiyo Tomiyasu Award. He has been an IEEE fellow since 2014, an AAAS fellow since 2020, ACM Fellow since 2024, an IEEE Distinguished Lecturer from 2015 to 2018, and an ACM Distinguished Speaker from 2022-2025. Dr. Han is also a 1% highly cited researcher since 2017.
Abstract: This speech explores the transformative potential of Generative AI (GAI) across various domains. Firstly, we examine the use of Large Language Models (LLMs) in repeated games to develop practical strategies aligning with the folk theorem's equilibrium conditions, enhancing cooperative behavior through future payoff considerations. Secondly, we address low-light image enhancement in teleoperation using diffusion-based AI-generated content (AIGC) models. A Vision Language Model (VLM)-empowered contract theory framework optimizes AIGC task allocation and pricing under information asymmetry, improving resource management for teleoperators and edge servers. In the realm of autonomous driving, we integrate Federated Learning (FL) with Vision-language models (VLMs) in Graph Visual Question Answering (GVQA), highlighting advancements in privacy preservation, reduced communication costs, and maintained model performance. Lastly, an LLM-based semantic communication (SC) framework for underwater communication is presented, demonstrating efficient data transmission and resilience against noise and signal loss by performing semantic compression and prioritization of image data. These innovations collectively illustrate the broad impact of AI technologies, shaping strategies, and enhancing applications across various fields.
Biography: Zhu Han received the B.S. degree in electronic engineering from Tsinghua University, in 1997, and the M.S. and Ph.D. degrees in electrical and computer engineering from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2002, he was an R&D Engineer of JDSU, Germantown, Maryland. From 2003 to 2006, he was a Research Associate at the University of Maryland. From 2006 to 2008, he was an assistant professor at Boise State University, Idaho. Currently, he is a John and Rebecca Moores Professor in the Electrical and Computer Engineering Department as well as the Computer Science Department at the University of Houston, Texas. Dr. Han is an NSF CAREER award recipient of 2010, and the winner of the 2021 IEEE Kiyo Tomiyasu Award. He has been an IEEE fellow since 2014, an AAAS fellow since 2020, ACM Fellow since 2024, an IEEE Distinguished Lecturer from 2015 to 2018, and an ACM Distinguished Speaker from 2022-2025. Dr. Han is also a 1% highly cited researcher since 2017.
Prof. Hao Zhang
the National "Ten Thousand Talent Program"
Innovative and Entrepreneurial Talents
New Century Excellent Talents
Ocean University of China, China
Speech Title: Key Technologies and
Large scale Promotion of Marine Applications of Beidou Satellite
Navigation System
Abstract: The Beidou marine application carries the dual mission of becoming a "maritime power" and "Beidou industrialization" national strategies, with urgent demand and significant significance. In response to the challenges faced by Beidou applications in complex marine environments, such as insufficient three-dimensional coverage, reduced positioning accuracy, and decreased success rate of short messages, since 2012, with the support of major national science and technology projects, we have broken through key technologies for Beidou ocean depth applications in all domains and sea conditions, and formed systematic innovation achievements from theory, technology, chips, products to standards, catalyzing fundamental changes in the use of Beidou systems in the marine field from basic functional services to comprehensive services.
Biography: Hao Zhang is a Professor and Doctoral Supervisor at Ocean University of China. He has been honored with prestigious national and provincial distinctions, including the National "Ten Thousand Talent Program", Innovative and Entrepreneurial Talents of the Innovation Talent Promotion Program by the Ministry of Science and Technology, New Century Excellent Talents by the Ministry of Education, and the Natural Science Outstanding Youth Fund of Shandong Province. His accolades also encompass the First Prize of Shandong Provincial Science and Technology Progress Award, First Prize of Satellite Navigation and Positioning Science and Technology Progress Award, and First Prize of Qingdao Science and Technology Award (Natural Science).
His research focuses on marine communication systems, MIMO communication systems, BeiDou Satellite Navigation and Positioning System, and novel marine observation and detection platforms. He has authored over 200 high-quality papers in top-tier international journals such as IEEE Transactions on Wireless Communications and IEEE Transactions on Communications, with all publications indexed by SCI/EI. Additionally, he holds 25 granted invention patents.
Abstract: The Beidou marine application carries the dual mission of becoming a "maritime power" and "Beidou industrialization" national strategies, with urgent demand and significant significance. In response to the challenges faced by Beidou applications in complex marine environments, such as insufficient three-dimensional coverage, reduced positioning accuracy, and decreased success rate of short messages, since 2012, with the support of major national science and technology projects, we have broken through key technologies for Beidou ocean depth applications in all domains and sea conditions, and formed systematic innovation achievements from theory, technology, chips, products to standards, catalyzing fundamental changes in the use of Beidou systems in the marine field from basic functional services to comprehensive services.
Biography: Hao Zhang is a Professor and Doctoral Supervisor at Ocean University of China. He has been honored with prestigious national and provincial distinctions, including the National "Ten Thousand Talent Program", Innovative and Entrepreneurial Talents of the Innovation Talent Promotion Program by the Ministry of Science and Technology, New Century Excellent Talents by the Ministry of Education, and the Natural Science Outstanding Youth Fund of Shandong Province. His accolades also encompass the First Prize of Shandong Provincial Science and Technology Progress Award, First Prize of Satellite Navigation and Positioning Science and Technology Progress Award, and First Prize of Qingdao Science and Technology Award (Natural Science).
His research focuses on marine communication systems, MIMO communication systems, BeiDou Satellite Navigation and Positioning System, and novel marine observation and detection platforms. He has authored over 200 high-quality papers in top-tier international journals such as IEEE Transactions on Wireless Communications and IEEE Transactions on Communications, with all publications indexed by SCI/EI. Additionally, he holds 25 granted invention patents.
Keynote Speakers of ICCSN2024
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Prof. Jiangzhou Wang |
Prof. Zhu Han |
Prof. Wei Xiang |