Please find below the list of the accepted workshops.
Title: Advanced Sensor Array Antenna and Signal Processing Techniques
Keywords: Array antenna design, array signal processing, waveform diversity, multi-dimensional signal processing.
The sensor array antenna and signal processing technique plays an important role in electronic systems, including radar, sonar, navigation, medical imaging, et. al. Sensor array technique can be used for enhancing desired signal and mitigating nuisance signals. A great number of research groups are working on the related topics. Therein, the corresponding research topics are in the top-active and frontier all over the world. As the studied on the sensor array is developed, several novel sensor array frameworks are born, including the waveform diverse array, flying flexible array, massive multiple-input multiple-output, opportunistic array, and so on.
In this session, we are open to any array antenna design topics as well as array signal processing studies, with the applications in radar, sonar, communication, navigation, et. al. Potential topics include but are not limited to the following:
Wideband and high-gain antenna design
Array antenna miniaturization and decoupling technique
Sensor array beamforming
DOA or DOD estimation
Multiple-dimensional signal proceSparse signal recovery
Prof. Yanhong Xu, Xi'an University of Science and Technology
Yanhong Xu was born in Shandong Province, China, in 1989. She received the B.S. degree in electronic engineering and the Ph.D. degree in electromagnetic field and microwave technology from Xidian University, Xi'an, China, in 2012, and 2017, respectively. From 2018/01 to 2019/12, she was a Lecturer with the College of Communication and Information Technology, Xi'an University of Science and Technology, Xi'an, China. Since 2019/12, she was elected as an Associate Professor in the same institute. During a period from 2018/02 to 2020/02, she is a Postdoctoral Fellow in the State Key Laboratory of Terahertz and Millimeter Waves, City University of Hong Kong. Her research interests include array antenna theory, frequency diverse array, wideband antenna and millimeter wave antenna technology. She was elected as an expert of “Thousand Talents Plan” (Young) of Shaanxi Province in 2020.
Research Fellow-Weiwei Wang, Xi'an Institute of Space Radio Technology
Weiwei Wang was born in Shandong province, China. He received the B.S. degree in electronic engineering and the Master degree from China University of Petroleum in 2005 and 2008, respectively, and the Ph.D. degree in signal and information processing from Xidian University in 2013 in China. Since 2013, he serves in Xi'an Institute of Space Radio Technology where he is promoted as Senior Research Fellow. His research interests include spaceborne radar system design, synthetic aperture radar technique, multi-sensor array signal processing, and space-time adaptive processing.
Prof. Jingwei Xu, Xidian University
Jingwei Xu was born in Shandong province, China. He received the B.S. degree in electronic engineering, and the Ph.D. degree in signal and information processing, both from Xidian University, China, in 2010 and 2015, respectively. He is currently an Associated Professor at School of Electronic Engineering, Xidian University.From 2015 to 2017, he was a lecturer at National Key Laboratory of Radar Signal Processing, Xidian University. From 2017 to 2019, he was a Postdoctoral Fellow under "Hong Kong Scholar Program" at Department of Electronic Engineering, City University of Hong Kong. From 2019 untilnow, he held the Associate Professor position in current institute. From 2021, he is selected as elite Professor in Xidian University. His research interests include radar system modeling, multi-sensor array signal processing, space-time adaptive processing, multiple-input multiple-output radar, and waveform diverse array radar. He received the prize for excellent Ph.D. dissertation of the Chinese Institute of Electronics in 2017, also the excellent Ph.D. dissertation of Shannxi Province in 2018. He received the Young Outstanding Talents of Shanxi Province in 2020 and Youth Science and Technology New Star of Shaanxi Province in 2021. He currently serves as Associate Editor for IEEE Transactions on Aerospace and Electronic Systems.
Title: Machine Learning and Optimization for Edge Computing
With the explosive of the global mobile traffic, how to improve network quality of service and end-user quality of experience by effectively allocating heterogeneous network resources is a key issue to be solved urgently in future wireless networks.AI-assisted edge computing can be studied to effectively overcome problems such as high latency and traffic load caused by cloud computing. However, realizing cooperative allocation and intelligent optimization of network resources in edge computing is challenging, and there are still many important open research problems.
This workshop aims to bring together the research accomplishments provided by researchers from academia and the industry. The other goal is to show the latest research results in the fields of edge computing and machine learning. The focus of the workshop will be on a broad range of edge computing such as resource allocation, content delivery, signal processing, machine learning, and network optimization involving the introduction and development of new advanced theoretical and practical algorithms. Original research and review articles are welcome.
Assoc. Prof. Chao Fang, Beijing University of Technology
Chao Fang received his B.S degree in Information Engineering from Wuhan University of Technology, Wuhan, China, in 2009, and the Ph.D. degree with the State Key Laboratory of Networking and Switching Technology in Information and Communication Engineering from Beijing University of Posts and Telecommunications, Beijing, China, in 2015. He joined the Beijing University of Technology in 2016 and now is an associate professor. From August 2013 to August 2014, he had been funded by China Scholarship Council to visit Carleton University, Ottawa, ON, Canada, as a joint doctorate. Moreover, he is the visiting scholar of University of Technology Sydney, Commonwealth Scientific and Industrial Research Organization, Hong Kong Polytechnic University, Kyoto University and Muroran Institute of Technology.
Dr. Fang is the senior member of IEEE, and the vice chair of technical affairs committee in IEEE ComSoc Asia/Pacific Region (2022-2023). Moreover, he is the leading editors of Electronics and Symmetry special issues. He also served as the Session Chairs of ICC NGN’2015 and ICCC NMNRM’2021, and Poster Co-Chair of HotICN’2018. His current research interests include future network architecture design, information-centric networking (ICN), software-defined networking (SDN), big data for networking, mobile edge computing, resource management and content delivery.
Assoc. Prof. Zhuwei Wang, Beijing University of Technology
Zhuwei Wang received his B.S. and the Ph.D. degrees from the Beijing University of Posts and Telecommunications, Beijing, China, in 2005 and 2011, respectively. From 2008 to 2010, he was a Visiting Scholar with the Department of Electronic and Computer Engineering, University of California at San Diego, and from 2012 to 2014, he was a Postdoctoral Research Fellow with the Department of Electrical Engineering, Columbia University, New York City, NY, USA. He is currently an Associate Professor with the Beijing University of Technology, Beijing, China.
His research interests include networked control systems, edge intelligence, optimization design, and real-time applications such as AIoT, UAV and CCC. He has authored or coauthored more than 70 research papers in international journals and conferences including IEEE TRANSACTIONS ON COMMUNICATIONS, IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, IEEE INFOCOM, IEEE GLOBECOM, IEEE WCNC, IEEE ICC, and so on.
Dr. Hua-Min Chen, Beijing University of Technology
Hua-Min Chen received the B.S. in Electronic Information Engineering from Northeast University of China in 2005, and the Ph.D in Information and Communication Engineering from Southeast University of China in 2011, respectively. From 2010 to 2016, Dr. Chen worked on physical layer design of 4G/5G system as a technical assistant manager in MediaTek Inc. (Beijing), and participated in 4G Rel-11, Rel-12, 5G standardization.
Dr Chen’s research interests comprises physical layer design for wireless communication system, physical layer algorithm design of 5G system (channel estimation, MIMO design, beamforming and etc. ), and artificial IoT system development.
Assoc. Prof. Zhihao Qu, Beijing University of Technology
Zhihao Qu received his B.S degree from Nanjing University in 2009, and his Ph.D. degree from Nanjing University in 2018. He joined Hohai University in 2019 and now is an associate professor. Moreover, he was a visiting scholar of Hong Kong Polytechnic University from 2019 to 2020.
Dr. Qu is a member of IEEE and a member of CCF. He served as the Publication Chair of ICPADS 2020, the Publicity Chair of DPCS 2022, the Workshop Chair of ICFEICT 2022. He also served as the Technical Program Committee of WASA'2022, GlobeCom'2022, ICA3PP'2021, WASA'2021, INFOCOM workshop ICCN'2021, and ICFC'2020. His current research interests include federated learning, edge computing, and distributed machine learning.
Image processing and pattern recognition use computer technology and mathematical methods to carry out scientific research on the representation of image or video information, encoding and decoding, image segmentation, image segmentation, image analysis, image quality evaluation, target detection and recognition and stereo vision. The main research contents include: pattern recognition and security monitoring of image or video, medical or material image processing, evolutionary algorithm, artificial intelligence, rough set and data mining. It is widely used in face recognition, fingerprint recognition, optical character recognition, natural language processing and information management systems in many fields.
The aim of this workshop is to bring together the research accomplishments of image processing and pattern recognition provided by researchers from academia and the industry. The other goal is to show the latest research results in the field of image processing and pattern recognition. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews.
Prof. Huimin Lu, Changchun University of Technology
Huimin Lu graduated from Xi'an Jiaotong University and obtained her master's and doctor's degree in Computer Science and Technology in 2005 and 2010 respectively. She completed her research at the Postdoctoral Programme in Computer Science and Technology of Jilin University in 2014, and she was a visiting scholar at the University of Missouri-Columbia, USA from 2016-2018. She is a professor and vice dean at the School of Computer Science and Engineering of Changchun University of Technology, and a doctoral supervisor in Statistics, Data Science and Artificial Intelligence, and a master supervisor in Computer Science and Technology, and Electronic Information. Her research interests include Artificial Intelligence and Application, Data Analysis and Mining, Biometrics, Computer Vision and other fields. She has participated in a number of National Natural Science Foundation, and National 863 Program projects, and she also has presided over a number of scientific research projects such as the National Natural Science Foundation of China, the Natural Science Foundation of Jilin Province, key R & D, major R & D, and industrial technology R & D of Jilin Province. On the basis of these projects, she has published more than 50 academic papers indexed by SCI and EI, and obtained more than 10 patents and software copyrights. Moreover, she also got the Jilin Provincial Science and Technology Progress Award and the State Federation of Commerce Science and Technology Progress Award.
Title: Theory and Technology of Multi-domain Cooperative Localization of Wireless Signals in Complex Scenarios.
Wireless signal positioning technology has been widely used in many industrial and information technology fields such as wireless communication, smart city, radio astronomy, aerospace, seismic survey, automatic driving, national defense security and so on, and is playing an increasingly important role in them. However, in actual physical scenarios, the electromagnetic signal and channel environment are extremely complex, and there are many factors that restrict the performance of wireless signal localization. Multi-domain cooperative processing is an important way to improve the performance of wireless signal localization in complex electromagnetic environment.
This workshop is dedicated to publishing research papers related to "Theory and technology of multi-domain cooperative localization of wireless signals in complex scenarios", aiming at publishing innovative and cutting-edge theories and applications in this field.Potential topics include but are not limited to the following:
Theory and technology ofmulti-systemcooperativepositioning.
Theory and technology ofmultiple-target cooperativelocalization.
Direct position determination technique by using signal waveform information.
Wireless signal positioning and detection integration technology.
Wireless signal positioning and identification integration technology.
Theory and technology of cooperative localization in wireless sensor networks.
Theory and technology ofwireless cooperativepositioning based on machine learning.
Theoretical performance analysis for wireless cooperative localization.
Wireless positioning based on machine learning.
Assoc. Prof. Wang Ding, PLA Strategic Support Force Information Engineering University
WangDing received his bachelor's, master's and doctor's degrees from Information Engineering University in July 2004, July 2007 and December 2011 respectively.From January 2015 to January 2018, he worked as a postdoctoral researcher at Information Engineering University.He worked as an associate professor and doctoral supervisor in the School of Information Systems Engineering, Information Engineering University. He was supported from National Natural Science Foundation of China (Grant No. 62171469, Grant No. 62071029 and Grant No. 61772548), China Postdoctoral Science Foundation (Grant No. 2016M592989), Key Scientific and Technological Research Project in Henan Province (Grant No. 192102210092).His research interests includewireless signal cooperative localization and array signal processing. As the first/corresponding author, he published more than fifty papers in SCI source journal, and as the first author, he published five monographs.He won two second-class prizes and five third-class prizes for provincial and ministerial scientific and technological progress, and won the top article award in outstanding S&T Journals of China(F5000) in 2020.
Assoc. Prof. Jiexin Yin, PLA Strategic Support Force Information Engineering University
Jiexin Yin received her bachelor's, master's and doctor's degrees from Information Engineering University in June 2011, June 2014 and June 2018 respectively.She worked as a memberin the College of Information Systems Engineering, Information Engineering University, and as a postdoctoral researcher at Information Engineering University.Shewas supported from the National Natural Science Foundation of China (Grant No. 61901526), China Postdoctoral Science Foundation (Grant No. 2019M663997), and the military special projects.Her research interests includewireless signal cooperative localization and array signal processing. As the first/corresponding author, she published more than thirty papers in SCI source journal, and she published three monographs.She won one second-class prize and four third-class prizes for provincial and ministerial scientific and technological progress, and PLA excellent master's and doctoral dissertations. She won the 7th China Youth Scientific and Technological Innovation Award, and "Xiaoping Scientific and Technological Innovation Team" as the team leader.
Title: Artificial Intelligence and Its Cross-domain Applications
Artificial Intelligence is a new technical science that researches and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. Research in this area includes robotics, speech recognition, image recognition, natural language processing and expert systems. Since the birth of artificial intelligence, its theory and technology are increasingly mature, with the development of human society from information to intelligent, the application of artificial intelligence technology is deep into all walks of life in human society. The application fields of Artificial Intelligence include computer vision, natural language processing, intelligent robots, deep learning, data mining, etc. Specific application scenarios include but are not limited to intelligent architecture, agricultural crop phenomics, medical rehabilitation robots, virtual reality, Intelligent product design,art, etc.
The workshopaims to bring together research findings from academia and industry. Another goal is to showcase the latest research results of AI in the fields of intelligent architecture, agricultural crop phenomics, medical rehabilitation robotics, virtual reality, art and other cross-applications. Prospective authors are encouraged to submit relevant outstanding research papers, including reviews of theoretical approaches and practical cases.
Prof. Zhang Wenli, Beijing University of Technology
Zhang Wenli is a professor at the Faculty of Information Science, Beijing University of Technology. Research interests: Computer vision and pattern recognition; Application research of artificial intelligence technology in agricultural crop phenoomics, UAV inspection, intelligent architecture, bionic rehabilitation prosthesis and other interdisciplinary fields; Presided over and mainly participated in a number of key projects of Ministry of Education, Ministry of Science and Technology, Beijing Science and Technology Commission and Beijing Natural Science Foundation. Nearly five years and Chinese core journals published SCI/EI retrieval and so on over 20 papers, declare international/national invention patents, utility models, such as nearly 30 items.
Assoc. Prof. Zhuozheng Wang, Beijing University of Technology
Zhuozheng Wang received a Ph.D. degree in Circuit and System from Beijing University of Technology. He is a national public visiting scholar of Michigan State University and an expert of the Intelligent Building and Building Automation Committee of China Automation Society. His research area is EEG signal processing by using deep learning. He has presided over the Beijing Outstanding Talents Project, the National Natural Science Foundation of China, the Science and Technology Planning Project of the Beijing Municipal Education Commission, the Beijing Natural Science Foundation, and participated in numerous related projects such as the Science and Technology Planning Project of the Beijing Municipal Education Commission. On the basis of these projects, he has published dozens of papers and national invention patents in recent years. He has also served as an advisor for numerous competitions and has received numerous corresponding awards.
Title: Advances in Cyberspace Security
Keywords: Artificial intelligence in cyberspace security,deep learning, machine learning, Internet of Things,edge computing
The great development of computer networks and communication has allowed easier access to information. However, governments and businesses have been facing difficulties in developing their cyberspace security network issues, such as novel attacks, hackers, internet criminals, etc. Therefore, a large amount of money is being spent on protecting data and avoiding theft or intrusion. Along with the continuous development of artificial intelligence, this has helped researchers to propose effective attack and defense methods in cyberspace security to prevent attacks from hackers.
Prof. Haixia Long, Hainan Norma University
Haixia Long received the Ph.D. degree in lightindustry information technology and engineeringfrom Jiangnan University in 2010. She is currently a Professor with the School of Information Science and Technology, Hainan Normal University. Her research interests include deep learning, artificial intelligence and Cyberspace security.Moreover, she was a visiting scholar in the Department of Electrical Engineering and Computer Science at the University of Missouri-Columbiafrom 2016to 2017.
Title: Advanced RF and mm-Wave Circuits and Systems
High performance RF and mm-wave circuits and systems are highly required to boost the deployment of 5G/6G systems. This workshop calls for works demonstrating the most recent progress and contributions to design methods of RF and mm-wave circuits and systems for 5G/6G application. This workshop will focus on but not limited to the following parts. (1) Advanced RF and mm-wave transceiver front-end architectures. (2) Novel design methods for highly-efficient wideband and multi-band power amplifiers. (3) Linearization techniques of RF nonlinear circuits, including analog and digital predistortion methods. (4) Signal processing techniques for complex modulated signals. (5) Integrated design methods for RF and mm-wave circuits and systems based on advanced technologies.
Assoc. Prof. Weimin Shi, Chongqing University
Weimin Shi received the Ph.D. degree from the University of Electronic Science and Technology of China, Chengdu, China, in 2019. From 2019 to 2021, he was a Post-Doctoral Research Fellow with the Department of Electrical and Computer Engineering, The Hong Kong University of Science and Technology (HKUST), Hong Kong. He is currently an Associate Professor with the School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China. His current research interests include board level power amplifiers, MMIC power amplifiers, and CMOS mm-Wave integrated circuit design. He has published more than 50 papers on top journals in recent years including IEEE TMTT, IEEE TIE, IEEE TCAS1, etc. He won the first place of the 2018 IEEE International Microwave Symposium Student Design Competition "14th High Efficiency Power Amplifier".
Associate Researcher Fellow-Yong Gao, University of Electronic Science and Technology of China
Yong Gao received the PhD degree in electromagnetic field and microwave technology from the University of Electronic Science and Technology of China (UESTC), Chengdu, PR China, in 2019. From 2019 to 2021, he was a full-time Post-Doctor Researcher in electromagnetic fields and microwave technology with UESTC. Since 2021, he was working as an associate researcher fellow with UESTC. His research interests include nonlinear dielectric properties of high power microwave material. interaction mechanism between high power microwave and materials high power devices feature parameter extraction, passive intermodulation test technology, design of microwave devices, and microwave integrated circuits. He has published more than 20 papers on top journals in recent years including IEEE TMTT, IEEE TCAS2, TEEE AWPL, etc.
Title: Energy Sustainability in Field of IoT: From Perception Layer to the Application Layer
Keywords: Energy sustainability, IoT, perception layer, SWIPT.
The constraint on energy supply and the low energy efficiency hinder the prosperity of the applications in the Internet of Things (IoT). For one thing, most of the perception layer of IoT consists of wireless sensor networks (WSNs), which are featured by energy limitation. For another thing, some types of applications, such as fog computing, cloud computing etc., are also limited by the constraint energy budget or low energy efficiency. Recent years have witnessed large development of the energy sustainability technology in IoT from the perception layer to the application layer, such as the simultaneous wireless information and power transfer technology, task offloading mechanism in fog computing, intelligent-reflecting-surface-assisted wireless communications, etc. This workshop is dedicated to publishing research papers related to “Energy Sustainability in field of IoT: from perception layer to the application layer”, with the aim of publishing innovative and cutting-edge theories and applications in this field. Potential topics include but are not limited to the following:
Theory and technology in energy efficiency in WSNs;
Applications of the simultaneous wireless information and power transfer technology in the field of IoT;
Energy harvesting technology applied in IoT or WSNs;
Intelligent-reflecting-surface-assisted wireless communications in WSNs;
Deep-learning-based technologies in WSNs;
Energy efficient task offloading mechanism in Heterogeneous IoT;
Data offloading technology in hybrid fog-clouding computing.
Dr. Deyu Lin, Nanchang University/Nanyang Technological University
Deyu Lin: IEEE Member, ACM Member, CCF Member, and CIC Member, hereceived the D.E degree in Computer System Architecture from Xidian University, China in 2019 respectively. He is currently with School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, and with School of Software, Nanchang University, China, and School of Electrical and Electronic Engineering, Shanghai Jiao Tong University, China. Besides, He worked as a visiting researcher in School of Electronic and Electrical Engineering, University of Leeds, UK from Oct., 2017 to Oct., 2018. His research interests cover WSNs, IoTs,and Fog Computing.
Title: Blockchain and Post-Quantum Cryptography
Blockchain and Post-Quantum Cryptography (PQC) are two distinct but related fields in the realm of computer science and cryptography. Blockchain is a decentralized, digital ledger that allows for secure and transparent transactions between parties without the need for a trusted intermediary, while PQC refers to cryptographic theory and practice that aims to provide secure encryption methods that remain secure even after the emergence of quantum computers.
Quantum computers have the potential to break traditional cryptographic methods, including those used in blockchain technology. Therefore, the development of PQC is particularly important for blockchain security. The use of PQC algorithms in blockchain could provide a more secure and resistant system against quantum attacks.To implement PQC in blockchain, new cryptographic protocols based on PQC algorithms need to be developed and integrated with the existing blockchain architecture. This requires addressing not only the technical aspects of PQC algorithms but also the operational and economic implications of the proposed changes.One possible approach to incorporating PQC into blockchain technology is through a hybrid scheme that combines both traditional and PQC cryptographic techniques. This approach could offer a transitional solution as PQC algorithms are still under development and may not be efficient enough to be used in all aspects of blockchain. The development of PQC is critical for ensuring the security and long-term viability of blockchain technology, and the integration of PQC algorithms with blockchain requires careful consideration of technical, operational, and economic factors.
Assist. Prof. Guangfu Wu, Jiangxi University of Science and Technology
Guangfu Wu was born in Yushan, Jiangxi, China, in 1977. He received the B.S. degree in mathematics education from Wuyi University, Guangdong Province, in 2000, the M.S. degree from the School of Mathematical Sciences, Xiamen University, Xiamen, in 2008, and the Ph.D. degree from the School of Information Science and Engineering, Xiamen University, in 2012. Since 2016, he has been an Assistant Professor with the School of Information Engineering, Jiangxi University of Science and Technology. He is the author of more than ten articles, and more than ten inventions. His research interests include coding theory and cryptography, blockchain, and artificial intelligence. Dr. Wu became a member (M) of the Chinese Association for Cryptologic Research (CACR), in 2014.
Title: Urban Surveillance Radar: Fundamentals and applications
Keywords:Urban Surveillance Radar, Target Localization, Human Activity Recognition, NLOS Detection
Information collection with surveillance radar is a valuable ability in urban environments. Herein, surveillance radars have the capacities to infer information about building structures as well as the presence, behavior, and vital signs of human targets, both indoors and outdoors, even when they are around a corner. Due to the complicated electromagnetic phenomena in urban environments, such as diffraction and multipath reflection, etc., accurate information acquisition of targets in urban contexts is a challenging problem. Cutting-edge theory and technology are highly desired to improve the sensing ability of urban surveillance radar.
This workshop is dedicated to publishing research papers related to "Urban Surveillance Radar: Fundamentals and applications", aiming at publishing the state-of-the-art and the most recent advancements in urban environment sensing techniques and approaches. Potential topics include but are not limited to the following:
Through-the-wall radar imaging
Radar based non-line-of-sight target detection
Radar based human activity recognition
Vital signs monitoring with radar
Indoor target localization with radar
Vehicle-mounted millimeter wave radar
Other modern radar, such as reflective and transmittive metasurfaces
Associate Research Fellow-Shisheng Guo, University of Electronic Science and Technology of China
Shisheng Guo received the B.S. degree in communication engineering from the Nanchang Hangkong University, Nanchang, China, in 2013, and the Ph.D. degree in signal and information processing from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2019. He is currently an Associate Research Fellow with the School of Information and Communication Engineering, UESTC. He was supported from the National Natural Science Foundation of China (Grant No. 62001091). His research interests include through-the-wall radar and radar based NLOS target detection. He is a Member of IEEE, the Session Co-chair of ICAUS 2021, ICAUS 2022 and 2019 ICCAIS.
Prof. Yong Jia, Chengdu University of Technology
Yong Jia received his master's and doctor's degrees from University of Electronic Science and Technology of China in June 2010 and June 2014 respectively. He was a Visiting Researcher at the Center for Advanced Communications, Villanova University. Currently, he is a professor at Chengdu University of Technology, and he also is a candidate for academic and technical leader of Sichuan Province. He was supported from the National Natural Science Foundation of China (Grant No. 61501062) and Sichuan Science and Technology Program (Grant No. 2019YFG0097 and Grant No. 2022YFS0531). His research interests include through-the-wall radar detection, non-line-of-sight target detection, and radar based human activity recognition. As the first/corresponding author, he published thirteen papers in SCI source journal. He won one first-class prize of Sichuan Science and Technology Progress Award.
Qiang An, Fourth Military Medical University
Qiang An received his B.E., M.S. and Ph.D. degree from the Department of Biomedical Engineering, Fourth Military Medical University, Xi’an, China, in 2012, 2015 and 2019 respectively. He worked at the Antenna Research Lab, Center for Advanced Communication, Villanova University, Villanova, PA, USA, as a joint training Ph.D. student from February 2017 to September 2018. Currently, he worked as a Lecturer at Fourth Military Medical University. His research interests include radar imaging, radar indoor monitoring, deep learning and its application in radar signal processing.
Title: Research on Multi-source Fusion Navigation, Navigation and Communication Fusion Technology
Keywords: Navigation and position perception, navigation and communication fusion technology, indoor positioning, multi-source integrated navigation, information fusion
With the rapid development of location and navigation technology, location-based services bring better and better user experience to people. However, a single navigation source often can not meet the accuracy requirements of users, and is not robust and reliable, and in order to solve the problem that a single indoor positioning technology can not meet people's positioning requirements in complex environment, a multi-source integrated navigation technology is proposed. Compared with traditional single navigation source, multi-source integrated navigation can make full use of the advantages of each navigation source and provide the best location navigation service. Multi-source information fusion and multi-source fusion navigation technology are analyzed and summarized, and the commonly used multi-source fusion algorithms and performance evaluation of multi-source fusion navigation are described.
Prof. Yuanfa Ji, Guilin University of Electronic Technology
Yuanfa Ji works as a professor at Guilin University of Electronic Technology, received his doctorate from the National Astronomical Observatories of the Chinese Academy of Sciences. His research interests include satellite communications, satellite navigation, real-time dynamic positioning and navigation receivers. He is also a reviewer of journals such as Journal of Astronautics and Journal of Beihang University. In the past five years, he has presided over and participated in many scientific research projects, such as National Natural Science Foundation of China, Guangxi Key R&D Program, sme Innovation Fund of Ministry of Science and Technology and other scientific research projects. Published more than 100 academic papers, including more than 30 papers indexed by EI or SCI, and applied for more than 100 national invention patents and utility model patents. Currently researching projects: National Natural Science Foundation of China, National Defense Pre-research project, National major special project-Beidou Demonstration Application project and many other practical projects.
Title: Sensor Signal Processing in Indoor Environment
Keywords: Sensor signal processing, navigation and positioning, wireless communication, radar signal processing
With the development of the Internet of Things (IoT) technology, a large number of indoor application needs have been generated, as well as a large number of theoretical and methodological researches. Sensor signal processing in indoor environment is an important branch of the information society tide. Its research objects are indoor personnel (including pedestrians, staff, patients and other personnel), indoor robots, indoor drones and so on. The research mainly focuses on navigation and positioning for indoor personnel, and there are also special studies on posture detection for patients. The research of indoor robots and drones is also focused on autonomous navigation and positioning, as well as flight attitude detection for drones. Therefore, the adoption of MEMS (Micro Electro Mechanical Systems) sensor, visual SLAM (Synchronous Locating And Mapping), geomagnetic, WIFI, Bluetooth, UWB (Ultra Wide Band), Lidar, sound, lighting, Radar and other technologies, combined with the current powerful IoT technology, has formed a very distinctive indoor environment wearable sensor signal processing research boom. We have reason to believe that the development of indoor sensor technology in the future will bring people new experiences in life, such as: airports, shopping malls, hospitals, schools, exhibition centers and other large indoor buildings.
Prof. Ling-Feng Shi, Xidian University
Ling-Feng Shi, professor, doctoral supervisor in Xidian University. He received his Bachelor's degree in Radio from China Jiliang University in 1995. Master's degree in Circuit and System from Xidian University in 2003 and Doctor's degree in Electronic science and Technology from Xidian University in 2008. 2012-2013 Spent 10 months in technical exchange in LG Company, South Korea. From 2021 to 2022, he spent one year as a visiting scholar in the University of Glasgow. Currently, he is mainly engaged in the research of sensor signal processing, positioning and navigation, wireless communication and other fields. He has published more than 110 academic papers in journals, including more than 90 papers in journals, more than 20 papers in domestic and foreign conferences, and more than 70 papers indexed by SCI (more than 20 IEEE journal papers), nearly 20 EI indexed papers, more than 20 ISP indexed papers, 17 national authorized invention patents, 1 authorized utility model, 6 national invention patents applied, 2 invention patents transferred. He has won 2 second prize of provincial and ministerial science and technology progress award and 1 Outstanding teacher award in Xidian University. Now he is a senior member of IEEE, reviewer of more than a dozen SCI authoritative academic journals, Electronic Journal, China Journal of Posts and Telecommunications, Journal of University of Electronic Science and Technology of China, expert member of "863", science and Technology award review expert of Ministry of Education. "Torch" program expert, more than a dozen provinces, municipalities directly under the central government science and technology evaluation experts.
Title: Intelligent Signal Processing
Keywords: Signal processing, neural network, deep learning
This workshop is aimed to broadcast intelligent signal processing with its main field on signal processing, and also machine learning, deep learning, and so on. We welcome all contributors to talk about their study.
Prof. Xizhong Shen, Shanghai Institute of Technology
Xizhong Shen's main research interests are signal processing, artificial intelligence, signal detection and estimation, DSP, detection, ultrasound imaging, electronic product development, etc. The main courses offered: signal processing, DSP applications, advanced information technology based on computing, artificial intelligence, image processing, signals and systems, detection technology, electronic CAD, etc. In recent years, he has chaired aiDSP Academy team to develop relevant artificial intelligence algorithms and technologies based on signal processing, and has cooperated with a number of enterprises and many horizontal projects.
Title: Exploring the Cross-Disciplinary Applications of Artificial Intelligence and Machine Learning
The great success inmanyfieldshas achieved by artificial intelligence and machine learning recently, which has raised great concerns when deploying machine learning algorithms for real-world applications, especially in space physics, healthcare, art, transportation, education, agriculture and soon.
In this workshop, we aim to invite researchers and practitioners who engage the application studies in the fields ofartificial intelligence to share their achievements.
This workshop invites papers on the following topics including advances in the interdisciplinary of AI and ML, but not limited to：
Space Physics: data modeling, space physics event prediction, and so on.
Healthcare: disease diagnosis, drug discovery, and patient monitoring.
Life Sciences:genetic data analysis, medical imaging, and so on.
Art: art painting generation,music composition and artworkanalysis, and so on.
Transportation: Advanced Driver Assistance Systems (ADAS),driver behavior analysis, object detection and lane line detection.
Agriculture: Smart soil irrigation and monitoring, Plant disease detection,remotesensinginagriculture, and so on.
Prof. Bing Han, Xidian University
Prof. Bing Han is the professor at School of Electronic Engineering, Xidian University. She received the Ph.D. degree in Pattern Recognition and Intelligent System from Xidian University in 2007. She worded at Institute of Cognitive Neuroscience in University College of London from 2008 to 2009. Her research interests include pattern recognition, visual perception and cognition, computer vision and cross-disciplinary research between space physics and pattern recognition, and so on.
Title: Array Signal Processing
Keywords:Phased array, MIMO array, WDA array, FDA array, Massive MIMO array, reconfigurable reflective array, 4D MMW array, distributed aperture array, bi/multi-static array.
Array signal processing is a process of obtaining the interested parameters by enhancing the desired signal while suppressing the interfering signal via the information obtained from multiple sensors placed in space. Usually, it can be divided into two branches: beamforming and parameter estimation. At present, the array system has gradually developed from phased array and multiple-input multiple-output (MIMO) array to waveform diversity antenna (WDA) array or frequency diversity antenna (FDA) array. Also, the geometry form is evolved from single static, bi/multi-static to network.
Array signal processing has been widely used in communications, radar, navigation, telemetry, tracking, and command (TT&C), sonar and radio astronomy and other fields. Typical practical applications include massive MIMO array and reconfigurable reflective array for communication, 4-dimensional millimeter wave (4D MMW) array for autonomous vehicle, anti-jamming array for navigation, conformal array for TT&C, towed sonar array, square kilometer array (SKA) for radio messages, etc.
In this session, we are open to any optimization frameworks for the trade-off between high performance and low cost, efficient optimization algorithms for antenna selection and precise beam modulation, parameter estimation methods with high precision and high resolution, mainlobe/sidelobe interference suppression schemes in complex electromagnetic environments, robust processing methods in the presence of gain and phase mismatches, and fast processing technique for large-scale array dimensionality reduction. Potential topics include but are not limited to the following:
1）Low-cost array design and processing
2）Array geometry optimization
4）Array parameter estimation
6）Robust array signal processing
7）Reduced-dimensional array processing
8）Multi-dimensional array signal processing
Prof. Zeng Cao, Xidian University
Zeng Cao was born in Suizhou, Hubei, China, in March, 1979. He received the B.S., M.S. and Ph. D. degrees in signal and information engineering from Xidian University, Xi'an, China, in 2001, 2004, and 2008 respectively. From May 2012 to May 2013, he did research work as a visiting scholar in the Mathematic Department, San Francisco State University, California, USA. He is currently a Professor and PHD supervisor at the School of Electronic Engineering, Xidian University. His research interests include array signal processing, moving target detection, and real-time applications. More than forties papers written by him and his cooperators are indexed by SCI or EI. A monograph on "Digital Beamforming Technique of Phased Array Radar" has been published in 2017. Moreover, 25 Chinese patents and three software copyrightsare granted, and 5 of these patents have been authorized for application. The two prizesof Science & Technologyat the Province level have been awarded to him and his team in 2006 and 2013, respectively. The competition team with his guidance won the first prize in the National Award in the 2020 China Graduate Electronic Design Competition, and he was selected as an excellent instructor in 2020. His competition team won the first prize in the Shaanxi Province of "Challenge Cup" Shaanxi University Student Extracurricular Academic and Scientific Works Competition in 2021.
Title: Complex System Modeling and Its Digital Solutions
Summary: Logistics industry is a pillar industry related to the national economy. Its inefficient (not enough to information building) and disordered (not strong to intensive degree) operation is an important reason for the slow decline of China's logistics GDP (14.6%) into the bottleneck period, so that there is a significant gap compared with advanced logistics countries (GDP (8~9%)). In order to meet the needs of the digital development for the national logistics industry and break through the above bottlenecks, this project focuses on the land transportation segment of "Depot - Vehicle dispatching – Order delivery"，with " formalizing mathematical description problem for the normal mode modern logistics ", "vehicle dispatching/order delivery in multi-goal/multi-constraint/multi-element optimization algorithm" and "building high-speed/high-accuracy vehicle dispatching/order delivery support system " of these three scientific problems on theory and application technology research, aiming to make achievements in mathematical modeling (discrete mathematical description), core algorithm (intelligent calculation of multi-level mixed data structure) and application development (constructing of vehicle dispatching/order delivery support system); The research carries out the above research plan with 11 detailed steps; Fulfillingthe great vision of digitalization/precision/intelligence/efficiency/low-carbonization, and contributes to the huge needs of delicacy management and high-quality development of logistics industry; At the same time, it is expected to use for reference to the related areas such as cargo and shipping.
Prof. Kewei Chen, Ningbo University
Dr. Kewei Chen received his Ph.D. degree from Tokyo Institute of Technology in 2000, and was recognized and funded by IPA software in 2001. In 2002, he won the Prize of Excellent Paper in Fuzzy Science of Japan. In the past 25 years, he has participated in 19large-scale scientific research projects (7 of which are the core technology leaders) and published 26core papers in international top journals and international conferences. In 2018, as a high-level leading talent recruited by the Organization Department of Yuyao-city, Ningbo, Dr. Chen settled in two enterprises, Ningbo Intelligent Manufacturing Industry Research Institute (Robot Innovation Center) and Danian Technology Group, after that,successfully applied for national distinguishedexpert. In January 2020, he joined Ningbo University and worked as a distinguished professor in school of Mechanical Engineering and Mechanics, specializing in intelligent manufacturing and robot teaching and research. In March 2021, he was appointed as the director of the Institute of Advanced Intelligent Robots.
Reconfigurable Intelligent Surface (RIS) is an emerging technology of reconfiguring wireless propagation environments through passive and tunable signal controls. It can be used to improve received signal strengths, reduce the transmit power consumption, and combat eavesdropping in wireless networks. However, due to the “multiplicative” fading effects, it is not trivial to acquire channel state information (CSI) when the number of RIS elements is huge in the multi-antenna systems. Hence, it is crucial but difficult to design RIS-assisted communication, computing and localization techniques based on imperfect CSI in wireless networks. This special workshop is aimed to introduce the state‐of‐the‐art researches on performance analysis, algorithm design, systematic design and implementation of RIS-assisted wireless networks. Suitable topics for this workshop include, but are not limited to, the following areas:
Active and passive beamforming design in RIS transmissions
Joint trajectory and beamforming design for Aerial RISs in wireless networks
RIS aided localization and sensing based on perfect/imperfect CSI
Scheduling and resource allocation in RIS assisted edge computing systems
Joint design of RIS-based communication and channel estimation empowered by AI techniques
Robust and secure communications in RIS-assisted wireless networks
Prof. Gang Wang, Ningbo University
Gang Wang received the B.Eng. degree in electronic engineering from Shandong University, Jinan, China, in 2006, and the Ph.D. degree in electronic engineering from Xidian University, Xi’an, China, in 2011. He joined Ningbo University, Ningbo, China, in January 2012, where he is currently a full Professor. From June 2018 to June 2019, he was a Visiting Scholar with the University of Missouri, Columbia, MO, USA. His research interests include the area of target localization and tracking in wireless networks.
Dr. Wang was the recipient of the Natural Science Funds for Outstanding Young Scholars from the National Natural Science Foundation of China and the Natural Science Funds for Distinguished Young Scholars from Zhejiang Provincial Natural Science Foundation. He is an elected member of the Sensor Array and Multichannel Technical Committee of the IEEE Signal Processing Society. He serves as the Associate Editor for IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, and the Handling Editor for Signal Processing (Elsevier).
Assoc. Prof. Juan Liu, Ningbo University
Juan Liu received the Ph.D. degree in electronic engineering from Tsinghua University, Beijing, China, in 2011. From March 2012 to June 2014, she was a Postdoc Research Scholar in Department of Electrical and Computer Engineering, NC State University (NCSU), Raleigh, NC, USA. From February 2015 to February 2016, she was a Research Associate in Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology (HKUST), Hong Kong. Since March 2016, she has been with Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China, where she is an Associate Professor. Now she is focusing on the research topics on UAV communications, wireless caching and edge computing, and deep learning for large-scale wireless networks.
Assoc. Prof. Hua Chen, Ningbo University
Hua Chen received the M.Eng. degree and Ph.D. degree in Information and Communication Engineering from Tianjin University, Tianjin, China, in 2013 and 2017, respectively. He is now as an Associate Professor in Faculty of Information Science and Engineering, Ningbo University, China. His research interests include array signal processing, MIMO radar.