Seminar 1

Title: International Workshop on Security and Privacy for Deep Learning Models
Summary: In recent years, the rapid advancement of Artificial Intelligence (AI) has ushered in a new era of technological innovation, with deep learning models at its forefront. As AI applications become increasingly pervasive in various domains, concerns related to security and privacy have escalated. The intrinsic complexity of deep learning models, coupled with their ability to process vast amounts of sensitive data, has raised significant challenges in safeguarding these systems against potential threats and ensuring the privacy of individuals. It is imperative for the research community to address these issues comprehensively, fostering the development of secure and privacy-preserving deep learning methodologies. We invite researchers, academics, and practitioners to submit original contributions to the International Conference on Security and Privacy for Deep Learning Models. This conference aims to serve as a platform for disseminating cutting-edge research, sharing insights, and fostering collaboration in the realm of AI security and privacy. The conference will cover a wide range of topics, including but not limited to: lAdversarial attacks on deep learning models lPrivacy-preserving techniques for training and deploying models lExplainability and interpretability in secure AI systems lFederated learning for collaborative and privacy-preserving model training lEthical considerations in AI security and privacy lSecure deployment of deep learning models in real-world applications lThreat modeling and risk assessment for AI systems lRobustness and resilience of deep learning models against novel attacks Researchers are encouraged to submit high-quality papers that contribute novel insights and solutions to the challenges posed by security and privacy concerns in the realm of deep learning models. The conference aims to facilitate meaningful discussions and collaborations, driving the field towards a more secure and privacy-conscious future.
Keywords: Security and Privacy; Deep Learning; Federated Learning
Chair 1
Associate Professor Kongyang Chen, Guangzhou University

Academic Curriculum Vitae: Kongyang Chen is an Associate Professor at Institutes of Artificial Intelligence, Guangzhou University, China. He is the Vice Director of Guangdong Provincial Engineering and Technology Research Center for Big Data Security and Privacy Preservation, and also the Director of the Institutes of Artificial Intelligence Application at GZHU. Before that, he was a Postdoctoral Fellow at the Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China, supervised by Prof. Jiannong Cao. From 2014 to 2018, he was an Assistant Professor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. He received his PhD degree in computer science from the University of Chinese Academy of Sciences, China. His main research interests are artificial intelligence, edge computing, Internet of Things, mobile computing, etc. He has published over 60 papers in top conferences or journals such as IEEE INFOCOM, ACM MobiSys, IEEE TDSC, IEEE TMC, IEEE TPDS, ACM TOSN, etc. He has also served as general chairs, PC chairs, or TPC chairs for many international conferences.
jianhua yang
Chair 2
Associate Professor Jianhua Yang, Guangdong Polytechnic Normal University

Academic Curriculum Vitae: Jianhua Yang is an Associate Professor at Guangdong Technological Normal University. He obtained his PhD degree from Sun Yat-sen University and has previously conducted research at New York University supervised by Prof. Edward K. Wong and Prof. Yun-Qing Shi. He serves as a committee member of the Digital Media Forensics and Security Special Committee of the China Society of Image and Graphics and as the Local Arrangement Chair for the International Conference EAI SPNCE 2023. His primary research focus lies in multimedia information content security, encompassing artificial intelligence, novel methods in deep learning, and their applications in steganography and steganalysis. He has published over 20 academic papers in authoritative journals and conferences in the field, and holds four granted invention patents. Yang has led projects such as the National Natural Science Foundation of China Youth Fund, Postdoctoral Fund General Project, Guangdong Natural Science Foundation General Project, and the Central University Basic Research Business Fee. He also serves as a reviewer for journals such as TIFS, TCSVT, TMM, TIP, etc.
Seminar 2

Title: Research on Information Security, Network Security, and Privacy Protection in the New Era
Summary: The development of the world today is approaching the era of rapid development of information technology. From a positive perspective, the deep integration of the Internet and various industries has enabled China to successfully achieve rapid breakthroughs. From the opposite perspective, the problems of information security, network security, and privacy protection brought about by the prosperity and development of the Internet remain severe, and enterprise data, personal privacy, and other issues face widespread infringement. Further exploration is needed on issues such as information security, network security, and privacy protection. By strengthening control measures, optimizing basic conditions, innovating encryption technologies, and raising security awareness, information security and network security can be enhanced.
Keywords: Mobile communication security; Cyberspace security; Intelligent computing

zhang kun
Chair 1
Professor Kun Zhang, Hainan Normal University

Academic Curriculum Vitae: Hainan Normal University's School of Information Science and Technology, Department of Cybersecurity: professor, Ph.D., doctoral supervisor, Hainan Province high-level talent "Top Talent", Hainan Province " Nanhai Masters" youth project talent, Hainan Province "515" Engineering Talent Project third level candidate, Hainan Province Science and Technology expert, Guangdong Province Science and Technology expert, Guangxi Science and Technology expert, Sanya Municipal Party Committee key expert, CCF (China Computer Federation) senior member, CCF Computer Application Professional Committee executive member, CIE (Chinese Institute of Electronics) senior member, IEEE member, ACM member; presided over more than 40 vertical and horizontal projects, including National Natural Science Foundation projects, Hainan Provincial Natural Science Foundation, Hainan Provincial Key R&D Plan projects; published over 200 papers, of which more than 30 are SCI-indexed; obtained 17 national invention patents and 2 international invention patents; serves as an editorial board member of the SCI journal Physical Communication and editor-in-chief of the international journal Distributed Processing System; won 1 first prize and 1 second prize in Hainan Provincial Science and Technology Progress Awards.
Chair 2
Dr Chenyuan Feng, EURECOM

Academic Curriculum Vitae: Chenyuan Feng received the B.E. degree from the University of Electronic Science and Technology of China in 2016, and the Ph.D. degree from Singapore University of Technology and Design in 2021, respectively. She has been doing postdoctoral work at Eurecom, France since 2024 and at Shenzhen Key Laboratory of Digital Creative Technology from 2021 to 2023, respectively. Her research interests include edge intelligence, multimedia intelligence, and federated learning for future generation communication. She has published over 20 SCI/EI papers in top journals or conferences such as IEEE TWC, IEEE TCOMM, IEEE IoTJ, IEEE WCM, IEEE ICC, IEEE GLOBECOM, ICASSP, SECON, WCSP, WCNC, ICCT and IJCNN (including one ESI top 1% highly cited paper and one IEEE conference best paper). She obtained there national invention patents and one edited book related to federated learning in intelligent systems; earned the First Prize in Chinese Post-doctoral Innovation and Entrepreneurship Competition, one Gold and one Silver Awards in Chinese “Internet+” Innovation and Entrepreneurship Competition. She served as a TPC member in IEEE ICCT-2023, IEEE TrustCom-2023 and IEEE BigDataSE-2023, and also a Committee member in of Special Committee on Metaverse in Shenzhen City Computer Federation (SZCCF) since 2022. She also presided one National Natural Science Foundation project since 2023.
Seminar 3

Title: Trustworthy and Explainable Network Intrusion Detection
Summary: Trustworthy and explainable network intrusion detection is a critical research area aimed at ensuring robust and reliable detection and prevention of malicious activities that threaten the security of network systems. Network intrusion detection systems (NIDS) are essential tools that monitor and analyze network traffic to identify potential intrusions. However, traditional NIDS faces challenges such as high false alarms, low accuracy for complex intrusions, lack of explainability, and vulnerability to adversarial attacks. Trustworthy and explainable NIDS are expected to have the following properties: 1) High confidence, which means the NIDS can provide accurate and reliable detection results with low false alarms. 2) Robustness, which means the NIDS can defend or mitigate the impact of various adversarial attacks and malicious manipulations. 3) Explainability, which means the NIDS can provide clear and understandable explanations for the detection results and processes. The workshop aims to bring together researchers, practitioners, and industry experts to discuss and advance the frontiers of NIDS in the context of trustworthiness and explainability. The focus will be on addressing the emerging security, privacy, and transparency challenges in NIDS. The workshop will explore innovative methods and strategies to ensure that intrusion detection models are not only effective and efficient but also secure, privacy-preserving, and comprehensible to users. The ultimate goal is to foster the development of NIDS that are robust against adversarial attacks and transparent in their decision-making processes.
Keywords: Network Intrusion Detection; Trustworthy; Explainable

Chair 1
Dr Junjun Chen, Peking University

Academic Curriculum Vitae: Junjun Chen is an engineer at the Computer Center at Peking University. His research area focuses on machine learning and cybersecurity. He received his Ph.D. degree in computer science at the University of Beijing University of Chemical Technology in 2020. He has published over 30 papers in conferences or journals. He served as a reviewer for academic journals, such as IEEE-TAI, J SUPERCOMPUT, NCAA, and so on. He participated in some national projects, such as the National Future Internet Technology Infrastructure Project and the Artificial Intelligence Operator Standard Formulation and Compilation Platform Project.
qiang guo
Chair 2
Researcher Qiang Guo, Peking University

Academic Curriculum Vitae: Guo Qiang is an engineer at the Computer Center of Peking University. He received his master's degree from China University of Petroleum (Beijing), where he studied under Professor Zhiguang Wang. He is the deputy director of the Network Operations Office of the Computer Center at Peking University. The main research directions are computer networks, wireless networks, intelligent network operation, etc. He has published more than 20 academic papers in authoritative journals and conferences in this field. He participated as the technical backbone of the National Future Internet Technology Infrastructure Project, Artificial Intelligence Operator Standard Formulation, and Compilation Platform Project.
Chair 3
Researcher Zhongnan Fu, Peking University

Academic Curriculum Vitae: Zhongnan Fu is a senior engineer at the Computer Center of Peking University. He received his master's degree from Beijing Institute of Technology, where he studied under Professor Shuoying Chen. His main research directions are computer networks. He has published more than 20 academic papers in authoritative journals and conferences in this field. He participated as the technical backbone of the National Future Internet Technology Infrastructure Project, Artificial Intelligence Operator Standard Formulation, and Compilation Platform Project.
Seminar 4

Title: Deep Learning for Intelligent Scene Perception
Summary: Visual understanding and multi-modality representation fusion are essential to intelligent scene perception. With the rapid progress in machine learning technologies, there are tons of remarkable advances in intelligent scene understanding, whose performance and application fields are extended greatly. However, the complexity of scene could be a challenge for efficient perception. For some application as automatic drive, pedestrian re-identification and robot tracking, the performance and efficiency are typically affected by disturbances in the natural scene. How to efficiently combine information from visual and other modalities to enhance the robustness of perception systems under accidental perturbation and complexity issues is crucial and meaningful. 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 field of intelligent scene perception. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews.
Keywords: Computer Vision; Multi-modality Representation Learning; Intelligent Scene Perception and Application; Person re-identification; Deep Learning

zhigui liu
Chair 1 
Professor Zhigang Liu, Northeast Petroleum University

Academic Curriculum Vitae: Zhigang Liu, received a Ph.D. degree in Computer Resources and Information Engineering from Northeast Petroleum University, and was a visiting scholar with the Department of Electrical & Computer Engineering at National University of Singapore from 2018 to 2019. As a senior CCF member, he is currently the Department Director of Computer Science and Engineering, Northeast Petroleum University. His research interests include machine learning, computer vision, especially, data/label- and computation-efficient deep learning for visual recognition. He participated in the National Natural Science Foundation, Natural Science Foundation of Heilongjiang Province, Scientific and Technological Projects of Petro-China, and Youth Science Foundation of Northeast Petroleum University. Based on these projects, he published many academic papers. PC chairs for many international conferences.
Chair 2 
Associate Professor Zongshuai Zhang, Chinese Academy of Sciences

Academic Curriculum Vitae: Dr. Zongshuai Zhang is an associate professor with the Institute of Computing Technology, Chinese Academy of Sciences. He received the Ph.D. degree in computer science and technology from Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China in 2019. His research interests include Edge Intelligence, Multi-Access Edge Computing and Computility Grid. He has published two books, three book chapters, over 30 papers in telecommunications/computing journals and conference proceedings. He served as the Regional Chair of ICCC 2023, the Technical Co-Chair of IoTCIT 2023, the Workshop Co-Chair of IAIC 2023, the Session Chair and TC Member of ICCC 2022, TPC Member of ISCIT 2022. He has served as Editorial Board Member of Metaverse Journal, Youth Editorial Board Member of Intelligent Construction Journal and Computer Engineering Journal. He was awarded the Best Presentation Awards from ISCIT 2022, the Best Creativity Award of Microsoft Research Asia “Beijing Hackathon”, the Outstanding Researcher Award of Institute of Computing Technology, CAS, the Winning Award of 6GANA Network AI Challenge. He is a member of IEEE and IEEE SA/AISC, a senior member of CCF.
Seminar 5

Title: Data Security in Blockchain
Summary: As a typical decentralized application, blockchain technology can effectively solve the data security issues in traditional centralized systems. However, for blockchain technology to truly be implemented and used, in addition to the supervision of relevant national policies, there are also some practical problems in the core technology aspect. For example, the Byzantine Generals problem in consensus algorithms, privacy protection issues in on-chain storage, and execution vulnerabilities in smart contracts are all worthy of in-depth research. This workshop explores data security in blockchain, while also taking into account research on new consensus algorithms, communication topologies, and optimized storage in blockchain.
Keywords: Blockchain; Data Security; Privacy Protection; Consensus Algorithm

Associate Professor Xiaohong Deng, Gannan University of Science and Technology

Academic Curriculum Vitae: Xiaohong Deng, received a Ph.D. degree in Computer Application Technology from Central South University. He worked as an associate professor at the School of Information Engineering, Gannan University of Science and Technology. His research interests include Blockchain and Information Security. He participated in the National Natural Science Foundation, Natural Science Fund Project in Jiangxi province, etc. Based on these projects, he published more than 50 papers in important academic publications at home and abroad. At present, he is a peer reviewer of some academic journals on Blockchain and its application.
Seminar 6

Title: Data Security and Privacy Protection Strategy in Cloud Computing
Summary: In today's era of digitization, the rise of cloud computing technology has transformed our perceptions of data storage, processing, and sharing. This powerful computing paradigm provides businesses with flexible and scalable computing resources and introduces unprecedented opportunities for collaboration and innovation in various fields such as scientific research, healthcare and business cooperation. However, without appropriate security and privacy solutions designed for clouds, this potentially revolutionizing computing paradigm could become a huge failure. 
The rise of cloud computing enables many private data to be centrally stored on cloud platforms, which bring great convenience to users, while raises concerns about privacy leakage. One of the key challenges in this area is how to make full use of cloud computing while protecting user privacy. Privacy protection technology provides a solution to this problem. Using secure multi-party computation, homomorphic encryption, differential privacy, and other technologies can ensure secure data processing in the cloud environment and achieve a delicate balance between privacy and data utilization. 
Cloud computing and privacy protection complement each other to build a secure, efficient, compliant data processing and storage environment. We will discuss how to maximize the full value of the cloud while protecting user privacy at the workshop.
Keywords: Cloud Computing; Privacy Protection; Secure Multi-party Computation; Homomorphic Encryption; Differential Privacy

en zhang
Professor En Zhang, Henan Normal University

Academic Curriculum Vitae: En Zhang received the Ph.D. degree from Beijing University of Technology, in 2013. From 2014 to 2016, he worked as a Postdoctoral Researcher at the Institute of Information Engineering, Chinese Academy of Sciences. He is currently a Professor with Henan Normal University. His research interests include cryptographic protocol design, secure multi-party computation, privacy protection and blockchain. He has presided over more than 20 national and provincial projects, such as the National Natural Science Foundation of China, the sub-project of the National Key Research and Development Program of the Ministry of Science and Technology, the project of the high-end foreign experts of the Ministry of Science and Technology and has authorized 16 invention patents. He has published more than 80 refereed publications including papers that have appeared in ACM CCS, Information Sciences, Neurocomputing, Iet Information Security, Security and Communication Networks, and Chinese Journal of Electronics.
Seminar 7

Title: Multi-mode Data Processing, Information Analysis, Complex Networks, Large Language Model and Information Service Application
Summary: The research is mainly aimed at the demand for new quality and new domain information services in the fields of science and technology, industry and informatization, scientific and technological innovation entities, and the public's scientific and technological information. Based on the open source data acquisition technology, multilingual and multimodal scientific and technological intelligence content identification, heterogeneous scientific and technological intelligence information fusion, intelligence reasoning and analysis platform research, complex networks and complex systems, social networks, large language model and information service application. Focusing on multi-mode technology competitive information tracking and cutting-edge trend analysis, the research mainly forms scientific and technological information service solutions and demonstration system platforms for different users and fields, and carries out application demonstration around strategic cutting-edge (choke) scientific and technological development support, commercial scientific and technological innovation services, public welfare scientific and technological intelligence information query services, etc. in the fields of science and technology, industry and informatization. * Multi Source Data Collection * Data Fusion and Data Analysis * Intelligence Knowledge Extraction * Scenario Construction * Demonstration and Promotion * Complex Networks and Complex Systems * Social Networks * Large Language Model * Information Service Application
Keywords: Technical Competitive Information; Application Demonstration; Multi-source Information Fusion; Complex Networks; Complex Systems; Social Networks

Associate Professor Sheng Hong, Beihang University

Academic Curriculum Vitae: Sheng Hong is an associate professor and doctoral supervisor in the School of Cyber Science and Technology at the Beihang University (BUAA). He engaged in network and information security, complex system security research, antagonistic sample generation technology, deep learning, generative adversarial network, completed a number of related scientific research projects in the field of network security, Presided over the national key basic research and development plan projects, national key research and development project, industrial Internet innovation and development project, technical basic project, pre-research project, National Natural Science Foundation of China There are more than 10 national, provincial and ministerial-level topics, and more than 10 horizontal topics in key industries such as industrial Internet, intelligent manufacturing, State Grid, and avionics systems. He is the editorial board member of several international journals and conferences, including "Information Network Security", "Information Technology and Network Security" and "Aeronautical Engineering Progress". In the national key research and development plan, he established a multi-level industrial network security protection model, through dangerous targets, key targets, cloud detection and other protection strategies and protective measures to ensure the network from the aspects of environmental credibility, situational knowledge, and controllable operation. Security; in the industrial Internet innovation and development project, he proposed a system security enhancement protection technology for the industrial Internet; in the National Natural Science Foundation, he broke through the critical phase change mechanism of fault propagation by focusing on the coupling, chaos and spreading characteristics of dynamic network faults The bottleneck of the maintenance control strategy provides a new solution for the prevention of complex dynamic network fault propagation and fault-tolerant control. In the open topic of the Shanghai industrial control system safety innovation functional platform, he aimed at the industrial Internet network suffered from virus attacks and equipment paralysis. The actual problems of the research network virus transmission mechanism and protection strategies. He has published more than 70 papers, including 30+ SCI papers, one co-authored academic book, and 14 national invention patents.
Seminar 8

Title: Advanced Optical Communications and Networking
Summary: With the rise of cloud computing technology, it has put forward higher requirements for the capacity of optical networks. To improve the transport capacity of optical networks, academia and industry have proposed some advanced optical communication and network technologies, such as multi-band and multi-core fiber technologies. Many challenging problems need to be solved in the new optical communication and network architecture. It will be interesting to work on solving these problems for the next generation of optical communications and networks. We invite researchers, academics, and practitioners to submit original contributions to the International Conference MICCIS 2024 on Advanced Optical Communications and Networking. This conference aims to serve as a platform for disseminating cutting-edge research, sharing insights, and fostering collaboration in the realm of optical communications and networking. The conference will cover a wide range of topics, including but not limited to: lAccess, Metro, and Core Optical Network Architectures lElastic Optical Communications and Networking lMulti-band Optical Communications and Networking lSpace Division Multiplexing Optical Communications and Networking lIntra and Inter Optical Data Center Networks lAdvanced Routing Strategies in IP over Optical Networks lOptical Network Control and Automation lSpectrum Efficiency, Resilience, and Security of Optical Networks
Keywords: Optical Communications; Optical Networks; Optimization Algorithms
Dr Xu Zhang, Chongqing University of Posts and Telecommunications

Academic Curriculum Vitae: Dr. Xu Zhang received the B.S. Eng. degree in 2014 and the Ph.D. degree in communication and information systems in 2019 from Northeastern University, Shenyang, China. From 2017 to 2018, he conducted academic research with the University of Tennessee, Knoxville, TN, USA. He is currently a Lecturer at the School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China. His research interests include software-defined networking, optical networks, computing force networks, and network optimization. He has authored or co-authored more than 25 technical papers in international journals and conferences. He was the recipient of the Best Paper Award of International Conference Qshine 2017. He is a life member of OPTICA. He also serves as a reviewer for journals such as JLT, OE, JNCA, etc.
Seminar 9

Title: Experience Enhanced Intelligence to IoT
Summary: The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. The main reason behind this interest is the capabilities of the IoT for seamlessly integrating classical networks and networked objects, and hence allows people to create an intelligent environment based on this powerful integration. However, how to extract useful information from data past produced by IoT, then transform such information into knowledge and facilitate standard knowledge reuse among different Things, are still open issues to be addressed. The Experience Enhanced Intelligence to IoT workshop is devoted to the experience-based methods addressing knowledge acquisition, representation, inference, and reusing problems and their application to IoT. We want to offer an opportunity for researchers and practitioners to identify new promising research directions as well as to publish recent advances in this area. The scope of this workshop includes, but is not limited to the following topics: •Theoretical framework for experience-based knowledge representation methods •Experience-based knowledge extraction algorithms for IoT •Dealing with Big Data and small data sets •Subsampling and feature selection in multiple model machine learning •Diversity, accuracy, interpretability, and stability issues •IoT-oriented methods in prediction and classification •Reusing, evolving, and online learning for IoT •Inference and reasoning using experience-based methods •Implementations of experience-based learning algorithms for IoT •Applications of intelligent IoT methods in medicine, security, industry, engineering, etc.
Keywords: Internet of Things; Signal Processing; Machine Learning; Experience-based Knowledge Extraction; Mobile Internet
Associate Professor Haoxi Zhang, Chengdu University of Information Technology

Academic Curriculum Vitae: Haoxi Zhang, is an Associate Professor from the Chengdu University of Information Technology, Chengdu, China. He received his Ph.D. degree in Knowledge Engineering from the University of Newcastle, Newcastle, Australia in 2013, and the master’s degree in Software Engineering from the University of Electronic Science and Technology of China. His research interests focus on representation learning, experience-oriented intelligent systems, knowledge representation and reasoning, computer vision, and deep learning. He has published more than 40 refereed papers in high impact factor journals and conferences.
Seminar 10

Title: Toward Intelligent Energy Efficiency Optimization and Low-Carbon Technologies in Cloud Computing
Summary: Cloud computing technology has been widely used to provide various services such as web, multimedia, gaming, and IoT applications for their advantages in hardware integration, resource configuration, and service isolation. With the rapid expansion in the scale and number of cloud computing services, the energy-saving and carbon management issues of cloud data centers have also attracted extensive attention in research and industrial communities. Artificial intelligence (AI)-based energy efficiency optimization is a newly emerged energy-saving paradigm that exploits machine learning, deep learning, and reinforcement learning models to explore the optimal energy-saving strategies and approaches of cloud computing systems. This workshop aims to provide an opportunity for collecting some works on AI-based energy efficiency optimization and low-carbon technologies of cloud data centers and their related fundamental infrastructure, including the latest research, development, and practical experiences as well as up-to-date issues, reviewing accomplishments, and assessing future directions and challenges in this field. It will bring researchers from academia and practitioners from industry to discuss the latest progress, new research topics, and potential application domains. Topics: The topics relevant to the workshop include (but are not limited to): 1. Applications of AI, big data, digital twins, and other technologies in reducing energy consumption for cloud data centers. 2. AI-based energy efficiency optimization and low-carbon technology for infrastructures related to cloud computing systems (communication network, base station, etc.) 3. Security assurance mechanism in green cloud data centers. 4. Carbon emission reduction-related techniques and solutions at the platform and system levels.
Keywords: Cloud Data Centers; Energy Saving; AI; Green Technology; Security

Dr Kaiyuan Bai, China Telecom Research Institute

Academic Curriculum Vitae: Kaiyuan Bai received his Ph.D. degree in mechanical engineering from Beijing Jiaotong University, Beijing, China, in 2022. He is currently an algorithm engineer with the AI Research Center at the China Telecom Research Institute (CTRI) in Beijing, China. His research interests include energy saving for data centers, machine learning, network intelligence, and expert systems. He has authored or co-authored more than 25 papers in SCI/EI journals and holds 2 patents. He currently serves as a reviewer for Information Sciences, Knowledge-Based Systems, Expert Systems With Applications, IEEE Transactions on Systems Man Cybernetics-Systems, et al. The "E-Energy Saving" product developed by his team has been deployed in 21 provinces in China, covering 148 data centers and saving 50.13 million kWh of electricity, equivalent to 32.30 million CNY for DC customers. This product won the "New Product Award" at the China International Big Data Industry Expo 2021. It was also selected for the "Recommended Catalogue of Energy-saving Technology Products in National Communication Industry (2021)" of the Ministry of Industry and Information Technology.
Seminar 11

Title: AI-Powered Android Malware Analysis: Strategies and Techniques
Summary: In today's digital landscape, the surge of Android malware poses a substantial threat, exploiting vulnerabilities in mobile devices and heightening risks to user privacy and data security. Recognizing the imperative for robust defense strategies, our workshop, "AI-Powered Android Malware Analysis: Strategies and Techniques," is a direct response to these evolving challenges. Designed to equip participants with a nuanced understanding of Android malware, the workshop integrates hands-on techniques and AI-driven insights to fortify digital defenses. This transformative exploration not only delves into the intricate world of Android malware but also fosters a collaborative space for professionals to share experiences and innovative approaches in the field of cybersecurity. Beyond theoretical knowledge, the workshop emphasizes practical application, enabling participants to directly apply AI-driven tools and strategies to real-world Android malware scenarios. Join this transformative exploration, connect with fellow professionals, and actively contribute to staying ahead in the dynamic realm of cybersecurity.
Keywords: Malware Analysis; Intrusion Detection System; Data Science; Deep Learning; Artificial Intelligence; Cybersecurity

Associate Professor Farhan Ullah, Northwestern Polytechnical University

Academic Curriculum Vitae: Farhan Ullah is an Associate Professor at Northwestern Polytechnical University (NPU) in Xi'an, Shaanxi, China. In 2020, he received a Doctor of Engineering in Computer Science (PhD) degree from the College of Computer Science at Sichuan University Chengdu, China. He is privileged to be ranked among the top 2% of scientists by Elsevier and Stanford University in 2023. He serves on the editorial boards and as an administrative member of various international journals and conferences. He received the Research Productivity Award (RPA) from COMSATS University Pakistan and the outstanding foreign faculty award from NPU in China. He was invited as a reviewer for several SCIE international journals, including IEEE Wireless Communications Magazine, International Journal of Intelligent Systems, Computers & Security, Computers and Electrical Engineering, and others. He has published 60+ SCI articles in several international journals. His research work has been published in various renowned journals of IEEE, Springer, Elsevier, Wiley, MDPI, and Hindawi.
Seminar 12

Title: Indoor navigation and positioning of IoT based on smartphones
Summary: Based on the powerful computing and efficient communication capabilities of smartphone sensor signal acquisition and processing, as well as the Internet of Things cloud, indoor navigation and positioning have become possible. Therefore, a large number of scholars have studied how to utilize the advantages of smartphones and the Internet of Things to conduct indoor autonomous navigation and positioning of MEMS sensors, RSS, WIFI, magnetic maps, visual SLAM, millimeter wave radar, ultrasound, RFID and other methods. It can be foreseen that this field will be a very hot research and application issue in the future.
Keywords: Sensor Signal Processing; Navigation and Positioning; Wireless Communication; Radar Signal Processing

Professor Ling-Feng Shi, Xidian University

Academic Curriculum Vitae: Assistant Engineer, Flight Automatic Control Research Institute, 1995-2000 Lecturer, College of Mechanical and Electrical Engineering, Xidian University, 2001- 2006; Associate Professor, College of Electrical Engineering, Xidian University, 2006-2014; Professor, College of Electrical Engineering, Xidian University, 2014- ; Master's Advisor in Automatic Control field, College of Mechanical and Electrical Engineering, Xidian University, 2006-2008 Master's Advisor in Circuit and System, College of Electrical Engineering, Xidian University, 2008- ; The 2nd International Conference On Mobile Internet, Cloud Computing and Information Security Ph. D Advisor in Circuit and System, College of Electrical Engineering, Xidian University, 2013-; Member of IEEE in December, 2018; Senior Member of IEEE in March, 2019; Visiting Scholar in LG Crop., South Korea, 2012-2013; Visiting Scholar in Glasgow University, UK,
Seminar 13

Title: Research on Uncertainty Quantification and Trustworthiness of Deep Neural Networks for Safety-Critical Systems
Summary: Advances in artificial intelligence are rapidly changing our world. Machine learning, deep learning, reinforcement learning and other techniques have permeated various academic disciplines and real-world applications, yielding significant achievements. Many autonomous systems heavily rely on deep learning models, often referred to as “black-boxes”for predictions. However, these deep learning models currently suffer from several limitations, such as potential incorrect predictions and failures in real-time scenarios. As a result, despite deep learning models have achieved superhuman performance on academic datasets, their progress in safety-critical real-world environments has been slow, such as autonomous driving, medicine and aeronautics and space systems. The most typical example is the car accident caused by Tesla's self-driving system in 2016. Before the deep learning method can be deployed on a large scale in security-critical systems, model trustworthiness issues must be addressed. Uncertainty quantification in deep learning fills this gap, and a well-calibrated uncertainty quantification model can tell whether a model is confident in its predictions. Therefore, the uncertainty quantification brings new opportunities for the safety-critical systems. In recent years, research on uncertainty quantification and evaluation, as well as trustworthiness and credibility in deep neural networks, have been receiving increasing attention. Welcome colleagues from various fields to participate in the discussion of this topic, and jointly build the broad application of neural networks in safety-critical systems.
Keywords: Safety-Critical Systems; Deep learning; Trustworthiness and Credibility; Uncertainty Quantification and Evaluation

bing gao
Dr Bing Gao, Beijing Institute of Control Engineering and Beijing Sunwise Information Technology Ltd

Academic Curriculum Vitae: Bing Gao received the Ph.D. degree from Beijing Jiaotong University in 2023 and the M.S. degree from Beijing Normal University in 2014. She is currently a high-trustworthiness artificial intelligence researcher at the Joint Laboratory of Beijing Institute of Control Engineering and Beijing Sunwise Information Technology Ltd. Her research interests include wired and wireless communication security, resilience control under malicious attacks and uncertainty quantification and trustworthiness in deep neural networks. She has presided over or participated in more than 10 national and Beijing city projects, including the Fundamental Research Fund for the Central Universities, the National Natural Science Foundation of China, the Beijing Natural Science Foundation, the Basic Science Research Fund for the Equipment Development Department of People's Republic of China Central Military Commission, the Frontier Research for the State Administration of Science, Technology and Industry for National Defense, the National Key Research and Development Program of China and the Project of China Aerospace Science and Technology Corporation. She has published more than 10 papers in top journals and conferences in the related field, such as ITS, ITSC and Control Theory and Applications.
Seminar 14

Title: Privacy Computing and Data Circulation
Summary: In the contemporary landscape of data-driven ecosystems, the workshop on "Privacy Computing and Data Circulation" explores the dynamic interplay between privacy computing technologies and the open, shared, and transactional aspects of data. This workshop aims to delve into the multifaceted challenges and opportunities surrounding the secure and trustworthy circulation of data in the context of privacy computing. Topics of Interest:   1.Ownership Delimitation in Privacy Computing: Investigating methodologies for defining data ownership boundaries using privacy computing techniques in the context of open data circulation. 2.Trustworthy Transactions in Data Circulation: Exploring mechanisms for ensuring trust in transactions associated with the open sharing and trading of data, particularly those leveraging privacy computing. Security Allocation Systems for Data Circulation: Discussing the establishment of secure allocation systems to safeguard data during its circulation in privacy-sensitive scenarios. 3.Trusted Data Governance for Data Circulation: Examining approaches to achieve reliable and transparent data governance specifically tailored for open data circulation scenarios. 4.Emerging Applications in Data Circulation: Unveiling innovative applications and use cases that leverage privacy computing for enhancing the efficiency and security of data open sharing, collaboration, and trade. 5.Privacy Metrics, De-identification Controls, and Data Circulation: Addressing the challenges and strategies related to privacy measurement, de-identification controls, and their impact on data circulation dynamics. Security Issues and Strategies for Data Elements: Delving into typical security concerns associated with data elements and proposing effective strategies for mitigating risks during open data circulation.
Keywords: Privacy Computing; Data Circulation; Trustworthy Transactions; Data Governance; De-identification Controls; Security Strategies

Assistant Professor Wenlong Tian, University of South

Academic Curriculum Vitae: Wenlong Tian is an Assistant Professor at the School of Computer Science, South China University of Technology. He earned his Bachelor's degree from the School of Computer Science, South China University of Technology, followed by a Master's degree and a Ph.D. in Computer Science and Technology from the School of Computer Science and Technology, Huazhong University of Science and Technology. He conducted research as a visiting scholar at Virginia Commonwealth University in the United States and pursued postdoctoral research at Nanyang Technological University in Singapore. He is a member of IEEE, ACM, and the China Computer Society. He has contributed to over 20 academic papers published in prestigious journals such as TDSC, IOTJ, JPDC, CCPE, TrustCom, IPCCC, HPCC, ICPADS, and various international conferences. Additionally, he holds more than ten national invention patents and was honored with the Best Paper Award at the IEEE TrustCom 2018 conference. His primary research interests include cloud computing security, blockchain and artificial intelligence security, cryptographic analysis, as well as parallel and distributed computing.
Seminar 15

Title: Secure and Trusted Enablement of Artificial Intelligence Applications in Mobile Internet and Cloud Computing
Summary: The rapid development of artificial intelligence technology, its application in the mobile Internet and cloud computing is becoming more and more extensive and in-depth, application-enabled security and trustworthiness issues are becoming more and more prominent. Large Language Modeling (LLM) has set off a revolution and innovation in the field of Natural Language Processing (NLP). The expansion of model parameters and pre-trained corpus empowers LLMs to excel in various types of NLP tasks. Despite the remarkable success of LLM systems in empowering industry applications, they can sometimes go against human values and preferences. In addition, well-designed adversarial cues may trigger LLMs to produce harmful responses. Even if not subject to adversarial attacks, current LLMs may generate inauthentic, toxic, biased, or even illegal content. These undesirable contents may be misused to generate undesirable social impacts. Therefore, there are many works in academia and industry dedicated to researching and solving these problems: 1.Factors influencing the secure and trustworthy application of artificial intelligence in mobile internet and cloud computing; 2.LLM system in mobile internet and cloud computing security risk classification system; 3.AI security and trustworthy system architecture in mobile internet and cloud computing; 4.AI model fusion to enable security in mobile internet and cloud computing; 5.System trustworthiness analysis of AI model fusion applications in mobile internet and cloud computing; 6.Others.
Keywords: AI Application Security In Mobile Internet; AI Application Security In Cloud Computing; AI Model Privacy Leaks; AI Harmful And Bias; AI Model Stability And Illusion; AI Simulation Attacks; AI Security And Trusted Enablement

Dr Nishui Cai, Institute of Security Technology

Academic Curriculum Vitae: Nishui Cai received his PhD from Shanghai Jiaotong University, China. He is currently working in China Telecom. His research interests include artificial intelligence, system reliability, system trustworthiness analysis, cyberspace security, data security, personal information protection, cloud security, cryptocurrency, application security, and AI security. In the past two years, he has published more than 10 SCI/EI papers in the field of cyberspace security, and more than 20 patent authorizations and applications.
Seminar 16

Title: Research on Cost-Effective AI-Empowered Cloud/Edge Computing Deployment in Intelligent Manufacturing Scenarios
Summary: The development of Industry 4.0 and the growing immersion of Artificial Intelligence (AI) in manufacturing have led to significant transformations in industrial operations. However, such developments bring forth unprecedented challenges associated with implementing efficient, robust, cost-effective, and low-carbon computing frameworks. For example, how to explore and formulate effective strategies for AI-empowered Cloud/Edge computing deployment in intelligent manufacturing scenarios to address these challenges. Moreover, how to concentrate on devising an optimal computational task distribution model between the cloud and edge computing layers, where the model will take into consideration a slew of factors including, but not limited to, latency, bandwidth, transmission and processing power, energy consumption, carbon reduction, and overall cost. To ensure an equitable distribution of resources that caters to diverse manufacturing requirements without compromising operational efficiency and cost-effectiveness, this has become an attractive research area for both industry and academia. Therefore, we welcome submissions that explore various aspects of AI-empowered Cloud/Edge computing deployment in intelligent manufacturing, covering topics including, but not limited to: AI-empowered effective deployment strategy design, AI-empowered Cloud/Edge computing complex processing tasks in intelligent manufacturing scenarios, optimisation algorithms capable of making real-time, intelligent decisions on resource allocation, valuable insights into harnessing the potential of AI-empowered cloud and edge computing in intelligent manufacturing. Moreover, the findings will contribute to the scientific community's understanding of the convergence of AI, cloud computing, edge computing, intelligent manufacturing, IoT-edge-cloud integration, blockchain for intelligent manufacturing, optimisation theory and methods, advanced sensor network communications, etc., and their applications in Cloud/Edge computing in intelligent manufacturing
Keywords: Cloud Computing; Edge Computing, Artificial Intelligence; Blockchain; Intelligent Manufacturing

Associate Professor Wei Chen, Xi'an Jiaotong-Liverpool University

Academic Curriculum Vitae: Wei Chen currently serves as an Associate Professor in the School of Intelligent Manufacturing Ecosystem. Prior to joining XJTLU, I worked across academia as well as industry in China and overseas for over 12 years, including multiple Fortune 500 companies. Wei obtained his PhD in Mechanical Engineering from The University of Newcastle, Australia. As the principal investigator, Wei has been awarded multiple research grants from the National Science Foundation China, Ministry of Science and Technology P.R.C., Australian Research Council and industry bodies. Wei has published over 60 articles in internationally renowned journals, and received multiple provincial and national awards. Wei practices as a Chartered Mechanical Engineer and also serve as a panel member for a number of international journals. Wei’s research interests cover digital manufacturing, advanced sensing technology, numerical modelling and artificial intelligence.
Dr Bintao Hu, Xi'an Jiaotong-Liverpool University

Academic Curriculum Vitae: Bintao Hu is an assistant professor at the School of Internet of Things, Xi'an Jiaotong-Liverpool University, Suzhou, China. He received his B.Eng. degree in telecommunications engineering from Xiangtan University, Xiangtan, China, in 2015, M.Sc. degree in Data Communications in 2017 and Ph.D. degree in Electronic and Electrical Engineering in 2022, both from the University of Sheffield, UK. He attended the European Commission Decade project with Ranplan, Barcelona, Spain, in 2018. He has been working on multiple Euro Union Horizon and innovative UK projects during past a few years. He won the 2022 IEEE WCNC Student Travel Grant and the 2023 IEEE/ACIS ICIS Best Oral Presentation Award. He was also invited to be a technical programme committee for IEEE VTC 2023-Fall, IEEE WCNC 2024, ICASET 2024, ICDSP 2024, a reviewer for IEEE VTC 2019-Fall, etc. His current research interests include D2D/V2X/U2X communications, mobile edge computing, resource allocation, reinforcement deep learning, federated learning, and vehicular networking.

Dr Wenzhang Zhang, Xi'an Jiaotong-Liverpool University

Academic Curriculum Vitae: Dr. Wenzhang Zhang received her PhD at the University of Liverpool, in 2022. During her PhD, she participated in the wireless charging project collaborating with Liverpool Alder Hey Children Hospital and Innovate Orthopedics Ltd., respectively. She also assisted in applying for the smart city wireless charging project from Liverpool Sensor City. After joining Xi'an Jiaotong-Liverpool University in 2022, she applied for the RDF project to conduct research on metasurface-based wirelessly powered devices for green smart city application. She has been partially funded by the Higher Education Funding Council of the United Kingdom. She was shortlisted for the Best Student Paper in the IEEE EuCAP 2020 conference, won the Best Student Paper Award in IET Active and Passive RF Devices 2018, won the SMC-IoT 2023 Best Paper Award, and was invited to give a speech at the CM SIG 2020 Characteristic Mode Analysis Organization. She has also been invited to serve as a technical program committee member of IEEE EuCAP 2021, ICCCN 2024, CCISS 2024, and ICDSP2024. Her research interests include microwave wireless power transfer/energy harvesting systems, metamaterials/metasurface design, characteristic mode analysis, wearable/implantable device design and passive RF device design.
Seminar 17

Title: RIS Empowered Intelligent Communications, Sensing, and Computation
Summary: Future 6G wireless communication systems are expected to realize an intelligent communication, sensing, computing and software reconfigurable functionality paradigm, where all parts of device hardware will adapt to the changes of the wireless environment, and provide various high-accuracy sensing services, positioning, etc.  Furthermore. with the rapid development of wireless networks and Internet of things (IoT), emerging applications continue to appear, such as artificial intelligence (AI) task, immersive service, and digital twins. Those emerging applications have put forward higher demands on sixth generation (6G) networks for end-to-end information processing capabilities. In order to meet the higher performance demands, 6G will be an end-to-end information processing and service system, and its core functions will expand from information transmission to information collection, information computing and information application, providing stronger sensing, communication, and computation capabilities. Thus, this has led to the emergence of a fast-growing area, called joint sensing, communications, and computation. It is widely expected that the advancements in joint sensing, communications, and computation would provide a platform for implementing AI in 6G systems and solving large-scale problems in our society ranging from autonomous driving to personalized healthcare. However, one fundamental problem is how we implement AI, sensing, computing into the wireless communications. In the recent period, a brand-new technology was brought to the attention of the wireless research community, the “Reconfigurable intelligent surface (RIS)”. Following the recent breakthrough on the fabrication of programmable metamaterials, reconfigurable intelligent meta-surfaces have the potential to materialize the intelligent software-based control of the environment in wireless communication systems, when coated on the otherwise passive surfaces of various objects. Being a newly proposed concept going beyond massive MIMO, intelligent surfaces are low cost, ultra-thin, light weight, and low power consumption hardware structures that provide a transformative means of the wireless environment into a programmable smart entity. Therefore, we expect that to implement the ubiquitous intelligence, sensing, computing by leveraging the advance of the RIS. Achieving the goal of RIS-empowered joint communications, sensing, and computation with high communication efficiencies calls for the designs of new wireless techniques based on a sensing-communication-and-learning integration approach. The observation of the recent surge in relevant research and the emergence of many exciting opportunities motivate us to propose the workshop of “RIS Empowered Intelligent Communications, Sensing, and Computation”.
Keywords: Reconfigurable Intelligent Surface (RIS); Integrated Sensing and Communication; Joint Communications; Sensing; and Computation

Professor Yongjun Xu, Chongqing University of Posts and Telecommunications

Academic Curriculum Vitae: Yongjun Xu (Senior Member, IEEE) received the Ph.D. degree (Hons.) in communication and information system from Jilin University, Changchun, China, in 2015. He is currently a Professor with the Chongqing University of Posts and Telecommunications, Chongqing, China. He is also a Bayu Youth Scholar of Chongqing. From December 2018 to December 2019, He was a Visiting Scholar with the Utah State University, Logan, UT, USA. He has authored or coauthored more than 100 IEEE Journal/Conference papers and received the Outstanding Doctoral Thesis of Jilin Province in 2016. His current interests include C-V2X, intelligent mobile networks, heterogeneous networks, resource allocation, intelligent reflecting surface, energy harvesting, backscatter communications. He is the Editor of Physical Communication, EURASIP Journal on Wireless Communications and Networking, Digital Communications and Networks, Chongqing YouDian Daxue XueBao, and also a Reviewer for IEEE Transactions on Wireless Communications, IEEE Transactions on Industrial Electronics, IEEE Transactions on Intelligent Vehicles, IEEE Transactions on Vehicular Technology, IEEE Communications Letters, and China Communications. He is the Chair of ICCT 2023, ICCC 2020, WCSP 2021, and also a TPC member of many IEEE international conferences, such as Globecom, ICC, ICCT, WCNC, ICCC, and CITS.
Professor Chongwen Huang, Zhejiang University

Academic Curriculum Vitae: Chongwen Huang is with Zhejiang University as a Tenure-Track Young Professor. His main research interests are focused on holographic MIMO surface/reconfigurable intelligent surface, B5G/6G wireless communication, mmWave/THz communications, and deep learning technologies for wireless communications. He was a recipient of the IEEE Marconi Prize Paper Award in Wireless Communications and the IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award in 2021. He was also a recipient of the Singapore Government Ph.D. Scholarship, and PHC Merlion Ph.D. Grant 2016–2019 for studying in CentraleSupélec, France. In addition, he has served the Chair of some wireless communications flagship conference, including a Session Chair for 2021 IEEE WCNC and 2021 IEEE VTC-Fall, and a Symposium Chair for IEEE WCSP 2021. Since 2021, he has been serving as an Editor for IEEE Communications Letters, Signal Processing (Elsevier), EURASIP Journal on Wireless Communications and Networking, and Physical Communication.
Professor Zhaohui Yang, Zhejiang University

Academic Curriculum Vitae: Zhaohui Yang is currently a ZJU Young Professor with the Zhejiang Key Laboratory of Information Processing Communication and Networking, College of Information Science and Electronic Engineering, Zhejiang University, and also a Research Scientist with Zhejiang Laboratory. His research interests include joint communication, sensing, and computation, federated learning, and semantic communication. He received the 2023 IEEE Marconi Prize Paper Award, 2023 IEEE Katherine Johnson Young Author Paper Award, 2023 IEEE ICCCN best paper award. He was the Co-Chair for international workshops with more than ten times including IEEE ICC, IEEE GLOBECOM, IEEE WCNC, IEEE PIMRC, and IEEE INFOCOM. He is an Associate Editor for the IEEE Communications Letters, IET Communications, and EURASIP Journal on Wireless Communications and Networking. He has served as a Guest Editor for several journals including IEEE Journal on Selected Areas in Communications.
Seminar 18

Title: Research on the Application of 5G/6G Base Station Communication Technology and Energy Saving Algorithms in Mobile Internet
Summary: With the emergence of 5G and the anticipated advent of 6G technology, the mobile internet landscape is undergoing a transformative evolution. This shift heralds unprecedented levels of connectivity, speed, and reliability. The focus of this study is on the application of enhanced 5G/6G base station communication technology alongside energy-saving algorithms within the context of mobile internet. The objective is to investigate how these technologies can collectively enhance network performance while minimizing energy consumption, a pivotal aspect in today's sustainable technology landscape.This study aims to realize technological innovations pertaining to mobile internet and explore potentially viable solutions. Often, this enhanced 5G/6G performance comes at the cost of increased energy consumption. Against this backdrop, the integration of energy-saving algorithms becomes paramount to strike a balance between performance and sustainability. Our research aims to bridge this gap by exploring the application of 5G/6G base station communication technology in conjunction with energy-efficient algorithms, paving the way for a greener and more efficient future of mobile internet
Keywords: 5G; 6G; Base Station Communication; Energy Saving Algorithms; Mobile Internet; Sustainable Technology

Researcher Shuhao Zhang, China Mobile Design Institute

Academic Curriculum Vitae: Zhang Shuhao, an engineer at China Mobile Communications Design Institute, graduated with a master's degree in Communication Engineering from Beijing University of Technology. He mainly engages in 5G/6G mobile communication evolution technology, cutting-edge network planning research, wireless network hardware research, cloud computing, deep machine learning, and energy-saving algorithm research. He has conducted an analysis of 5G network coverage enhancement schemes for high-speed rail, studying issues such as 5G network coverage holes, cell switching, cell merging, and network design. Aiming at the queuing mechanism for user access to cloud computing centers, a cloud computing task queuing model is proposed, and based on this, a cloud computing center energy management algorithm based on the M/M/c queuing process is proposed.He participated in multiple National Natural Science Foundation projects, National Key Basic Research and Development Program projects, Industrial Internet Innovation and Development projects, and China Mobile Group's major key projects.Based on these projects,he published many academic papers and applied for many patents.
Seminar 19

Title: Sensing-Assisted Future Millimeter Wave Wireless Communications
Summary: Millimeter wave (mmWave) communication technology has the potential to provide high data rates, low latency, and support for new high-bandwidth applications. However, mmWave communications also present many challenges, including high path loss, blockage, and sensitivity to the environment. Sensing technologies have emerged as a solution to overcome these challenges, by utilizing information on the environment and the users' behavior to improve the performance of mmWave links and networks. For example, radar signals can be utilized to detect and track objects in the environment, providing information on the channel characteristics, path loss, and blockage. This workshop aims to bring together researchers and practitioners from both academia and industry to share their latest research outcomes and practical applications related to sensing-assisted mmWave wireless communication systems. Topics of interest include but are not limited to: (1) Sensing-based channel modeling, estimation, and prediction for mmWave systems (2) Sensing-assisted beamforming and tracking techniques for mmWave communications (3) Sensing-enhanced resource allocation and scheduling algorithms for mmWave networks (4) Sensing-aided mobility management and handoff for mmWave systems (5) Sensing-based security, privacy, and trust issues for mmWave wireless communications (6) Sensing-assisted integration of mmWave with other wireless technologies, e.g., Wi-Fi, cellular, and satellite communications (7) Sensing-based experimental prototypes and testbeds for mmWave wireless systems (8) Sensing-assisted applications and services enabled by mmWave wireless communications, e.g., autonomous vehicles, smart grid, smart cities, and healthcare. Selected paper will be recommended to MDPI Electronics for potential fast-track publications.
Keywords: Millimeter-wave Communications; Radar Sensing

Dr Qing Xue, Chongqing University of Posts and Telecommunications

Academic Curriculum Vitae: Qing Xue received the Ph.D. degree in information and communication engineering from Southwest Jiaotong University in 2018. She joined the School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, in 2018 as a Lecturer. From Dec. 2019 to Jan. 2024, she was a post-doctoral fellow with the National Key Laboratory of Wireless Communications, University of Electronic Science and Technology of China. From Dec. 2021 to Nov. 2023, she was also a post-doctoral fellow with the State Key Laboratory of Internet of Things for Smart City, University of Macau, under the Macao Young Scholars Program. Her research interests include millimeter wave communications, intelligent wireless networking, and resource management in mobile networks.
Professor Zhidu Li, Chongqing University of Posts and Telecommunications

Academic Curriculum Vitae: Zhidu Li received the PhD. degree in information and communications engineering from Beijing University of Posts and Telecommunications in 2018. He was with the Norwegian University of Science and Technology, as a Visiting Scholar in 2017. He is currently an associated professor with Chongqing University of Posts and Telecommunications. He is a member of the IEEE. His research interests include network calculus, wireless powered IoT, and edge intelligent. Dr. Li has published more than 50 papers in his research area, and most of them appeared in prestigious IEEE journals and conferences, such as IEEE JSAC, IEEE TMM, IEEE GLOBECOM, IEEE ICC and etc. He was the recipient of 3 best paper awards from conferences such as the IEEE WCSP, IEEE BLOCKCHAIN and EAI MOBIMEDIA. He is also the inventor and co-inventor of more than 15 patents and patent applications. He has also served as reviewers for IEEE JSAC, IEEE TMM, IEEE TWC, IEEE TCOM and etc.
Assistant Professor Yao Sun, University of Glasgow

Academic Curriculum Vitae: Yao Sun is currently a Lecturer with James Watt School of Engineering, the University of Glasgow, Glasgow, UK. Dr. Sun has extensive research experience and has published widely in wireless networking research. He has won the IEEE Communication Society of TAOS Best Paper Award in 2019 ICC, IEEE IoT Journal Best Paper Award 2022 and Best Paper Award in 22nd ICCT. He has been the guest editor for special issues of several international journals. He has served as TPC Chair for VTC 2024, UCET 2021, and TPC member for a number of international flagship conferences, including ICC , VTC GLOBECOM, WCNC. His research interests include intelligent wireless networking, semantic communications, blockchain system, and resource management in next generation mobile networks. Dr. Sun is a senior member of IEEE.
Seminar 20

Title: Integrated Sensing, Communications, and Security
Summary: Understanding wireless sensing capability provides a natural opportunity to pursue the integration and coordination gains, making sensing and communication co-design a strong desire in the future mobile computing devices. Following this trend, the sensing and communication layers in traditional IoT devices are changing from separation to integration. This type of research is normally referred to as Integrated Sensing and Communications (ISAC). Jointly envisioned by next-generation communication standards (B5G and 6G), various research problems related to ISAC need to be addressed that cover a wide range of disciplines, including resource optimization, green network architecture, transceiver protocol, etc. However, there is an intense discussion in progress in the wireless community on possible alternative approaches to secure the B5G and 6G wireless edge, building on the premise that the properties of the wireless medium can be exploited in building novel security approaches. The area of physical layer security (PLS) is gaining momentum in this framework, with the hope that it can play a vital role in reducing both the latency as well as the complexity of novel security standards. The aspiration of the present special issue is to provide the platform for presenting cutting-edge novel results in combining PLS with ISAC and its potential application in B5G and 6G systems, as well as high quality tutorial articles on related topics.
Keywords: Integrated Sensing and Communications; Resource Optimization; Physical Layer Security; Securing the B5G and 6G

Dr. Kan Yu, Beijing University of Posts and Telecommunications

Academic Curriculum Vitae: K. Yu is with the School of Computer Science and Engineering, Macau University of Science and Technology, Taipa, Macau, 999078, P. R. China; the Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, 100876, P.R. China. His main research interests include wireless networks, IoT security, and distributed algorithm design and analysis. Dr. Yu is a member of the IEEE and the China Computer Federation (CCF).