Invited Speakers of ICCSN2025

Prof. Wenxin Liu, Aerospace Information Innovation Institute of the Chinese Academy of Sciences, China

Biography: Wenxin Liu (SM’2015), a researcher of the Aerospace Information Innovation Institute of the Chinese Academy of Sciences, a professor and doctoral supervisor of the University of the Chinese Academy of Sciences, IET Fellow, an associate editor of IEEE Access, a senior member of IEEE, and a chief scientist of the national key research and development program, has long been engaged in the research of millimeter wave terahertz vacuum electron radiation sources. Hosted more than 30 projects including the National Key Research and Development Program, the National Natural Science Foundation of China, the Chinese Academy of Sciences' important direction, and the 863 Program. Achieved the first prize and 3 second prizes for military scientific and technological progress, 1 first prize for scientific and technological invention in China's non-ferrous metal industry, 1 second prize for scientific and technological progress of the Chinese Society of Electronics, and the Outstanding Contribution Award at the 5th International Conference on Materials Microanalysis in 2019. In the past 5 years in Light: 31 SCI papers have been published in journals such as Science&Applications, IEEE Tran. MTT, IEEE EDL, and the International Vacuum Electronics Conference (IVEC), with 70 papers included in EI. He has cited 348 times and authored 1 monograph. He has given 30 invited presentations at important academic conferences such as IRMMW THz, IVEC, and PIERS; Authorized 9 national invention patents and 5 software copyrights; Served as chairman of international and domestic conferences and TPC committee member 26 times; Train 30 graduate students, including 12 doctoral students and 18 master's students (including joint training). Expert in the evaluation of major scientific instruments by the National Natural Science Foundation of China, expert in the evaluation of key research and development plans by the Ministry of Science and Technology, expert in the evaluation of graduate theses by the Ministry of Education, and editorial board member of the Journal of Terahertz Science and Electronic Information. Twice awarded the title of "Excellent Science and Technology Worker" by the Chinese Electronics Society and selected for the "Elite Talents" program by the Institute of Electronics, Chinese Academy of Sciences.

Prof. Feng Yin, The Chinese University of Hong Kong, Shenzhen, China

Biography: Feng Yin received his B.Sc. degree from Shanghai Jiao Tong University, China, and his M.Sc. and Ph.D. degrees from Technische Universitaet Darmstadt, Germany. From 2014 to 2016, he was a postdoc researcher with Ericsson Research, Linkoping, Sweden. Since 2016, he has been with The Chinese University of Hong Kong, Shenzhen and is currently an assistant professor of the School of Science and Engineering. His research interests include statistical signal processing, Bayesian learning and optimization, and sensory data fusion. He has published more than 40 top-tier journal papers, 50 conferences, and 20 patents/standards. He was a recipient of the Chinese Government Award for Outstanding Self-Financed Students Abroad in 2013 and the Marie Curie Young Fellowship from the European Union in 2014. He was the finalist for the IEEE CAMSAP best paper award in 2013 and received the best paper award of ICSINC conference in 2022. He has served as Associate Editor for the Elsevier Signal Processing Journal and currently serving as the Associate Editor for the IEEE Transactions on Signal Processing. He is an IEEE senior member and a core member of the IEEE Machine Learning and Signal Processing (MLSP) technical committee and the IEEE SPS scholarship committee.

Prof. Ning Wang, Zhengzhou University, China

Biography: Ning Wang received the B.E. degree in communication engineering from Tianjin University, Tianjin, China, in 2004, the M.A.Sc. degree in electrical engineering from the University of British Columbia, Kelowna, BC, Canada, in 2010, and the Ph.D. degree in electrical engineering from the University of Victoria, Victoria, BC, Canada, in 2013. From 2004 to 2008, he was with the China Information Technology Design and Consulting Institute as a Mobile Communication System Engineer, specializing in telecommunication network traffic analysis and radio network planning and optimization. From 2013 to 2015, he was a Postdoctoral Research Fellow with the Department of Electrical and Computer Engineering and the Institute for Computing, Information and Cognitive Systems, the University of British Columbia. Since 2015, he has been with the School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China, where he is currently a full Professor and Chair of the Department of Communication Engineering. He also holds adjunct appointments with the Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada, and the State Key Laboratory of Millimeter Waves, Southeast University, Nanjing, China. In 2017, he was a Visiting Scholar in the Department of Electronic Engineering, Tsinghua University, Beijing, China. His research interests include resource allocation and security designs of cellular networks, channel modeling for wireless communications, statistical signal processing, and cooperative wireless communications. He serves as the Deputy Secretary-General of the Intelligent Transportation Information Engineering Society of the Chinese Institute of Electronics. He has also served on the technical program committees of international conferences including the IEEE GLOBECOM, IEEE ICC, IEEE WCNC, ICICC and CyberC.

Prof. Qinghua Luo, Harbin Institute of Technology (Weihai), China

Biography: Luo Qinghua is a Professor and Doctoral Supervisor at Harbin Institute of Technology (Weihai). He serves as the Deputy Director of the Key Laboratory of Cross-Domain Collaborative and Integrated Support for Marine Unmanned Systems (Ministry of Industry and Information Technology) and Director of the Weihai Key Laboratory of Marine Intelligent Unmanned Equipment Technology. His research focuses on wireless positioning and uncertainty analysis, marine stereoscopic observation technology, intelligent unmanned systems, and collaborative positioning and navigation.

He has led over 20 research projects, including grants from the National Natural Science Foundation of China (General Program), Shandong Natural Science Foundation (General Program), Shandong Major Science and Technology Innovation Project, China Postdoctoral Science Foundation, Open Fund of State Key Laboratories, and industry collaborations. He has published more than 30 SCI/EI-indexed papers in journals such as IEEE Transactions on Industrial Informatics, Information Sciences, IEEE Sensors Journal, Sensors, Neural Computing and Applications, Measurement, Acta Automatica Sinica, and Journal of Software. Additionally, he holds 20 authorized national invention patents and has filed 36 patent applications.

Prof. Luo serves as a reviewer for several prestigious journals, including IEEE Transactions on Industrial Informatics, IEEE Transactions on Instrumentation & Measurement, Acta Electronica Sinica, and Acta Automatica Sinica. He is a member of IEEE, ACM, CCF, the Chinese Institute of Electronics, the Chinese Association of Automation, and the China Academic Degrees & Graduate Education Association.

Prof. Dr. Mohd Zulfaezal Che Azemin, International Islamic University Malaysia, Malaysia

Speech Title: High-Resolution Retinal Image Analysis: AI-Powered Diagnostics from Pixel to Prediction in a Cloud-Based Framework

Abstract: Retinal image analysis is a vital tool for the early detection of vision-threatening and systemic conditions such as diabetic retinopathy, glaucoma, and age-related macular degeneration. This talk introduces a high-resolution, cloud-based diagnostic framework that leverages artificial intelligence to enhance the precision and accessibility of retinal disease screening. Using 2048×2048 pixel fundus images from the FIVES dataset, the system applies fractal dimension (FD) analysis to quantify retinal vascular complexity, enabling robust differentiation between healthy and pathological states.
Central to the framework is a deep learning segmentation model (IS-Net) trained on high-resolution images, which achieves high specificity and F1 scores in identifying fine vascular structures. The system further integrates optic cup-to-disk ratio (CDR) analysis and diabetic retinopathy prediction using convolutional neural networks, creating a multifaceted assessment pipeline suitable for both clinical use and large-scale screening initiatives.
The entire solution is deployed via a cloud-based architecture, supporting real-time processing, remote access, and integration into teleophthalmology workflows. Usability testing among clinical users yielded high satisfaction scores, reinforcing the system’s practical readiness. These findings illustrate the critical role of high-resolution imaging and scalable AI deployment in building next-generation digital health tools aligned with emerging connected healthcare ecosystems.

Biography: Prof. Dr. Mohd Zulfaezal Che Azemin aspires to enhance healthcare through innovative research in medical image processing. With a Master's degree from Monash University and a Ph.D. from RMIT University, his expertise in analyzing retina images for stroke risk prediction has positioned him as a pioneer in his field. At the Kulliyyah of Allied Health Sciences, he merges theoretical knowledge with practical application in his teachings on optics, health informatics, digital image processing, and AI in Medical Imaging, fostering an environment of innovation among his students.

His contributions have been recognized with awards for research excellence and innovation, reflecting his commitment to making a tangible difference in the field. Dr. Zul's engagement with industry, leading to significant initiatives such as a Prototype Research Grant Scheme, and Industry Matching Programme further demonstrates the practical impact of his work.

Dr. Zul's global collaborations with renowned experts in Japan, Australia, China, Singapore, and Palestine have greatly enhanced his research, emphasizing the international significance of his contributions. Adding to his career experience, Dr. Zul has authored and co-authored articles in reputable journals, including the IEEE Transaction on Medical Imaging, Neurology, Neurobiology of Aging, Investigative Ophthalmology & Visual Science, Experimental Eye Research, and Fractal and Fractional. These publications showcase his wide-ranging impact on the fields of medical imaging, neurology, and ophthalmology.

Through persistence, collaboration, and a dedication to global scientific exchange, Dr. Zul exemplifies the qualities of a pioneering researcher in healthcare technology. His work not only advances the scientific community but also offers hope for better health outcomes worldwide.

Prof. Mohd Nazri Bin Ismai, National Defence University of Malaysia

Biography: Prof. Dr. Mohd Nazri became Lecturer at National Defence University of Malaysia. Prof. Dr. Mohd Nazri Ismail had a deep involvement in computer network research and was awarded the prestigious “Educator Award 2009 – R&D/Education category” by MARA (Malaysia Agency). He has supervised Ph.D. and Master Students and teaching at undergraduate and post graduate level. Assoc. Prof. Dr. Mohd Nazri Ismail has published more than 100 papers in national and international journals (indexed ISI, SCOPUS, IET) and IEEE conferences.
He has attended many international conferences throughout the world and has chaired many technical sessions. He has appointed as Technical Program Committee and organized more than 60 national and international conferences. He has appointed as Editorial Board member more than 90 international journals and 40 international reviewer panels (journal/proceeding). Awards and laurels won by Assoc. Prof. Dr. Mohd Nazri Ismail run into volumes and he has received 28 awards in R&D/Education. Assoc. Prof. Dr. Mohd Nazri Ismail is an International Association of Engineers (IAENG), IEEE Cloud Computing Community, Society of Digital Information and Wireless Communications (SDIWC), International Association of Engineers and Scientists (IAEST), Universal Association of Computer & Electronics Engineers (UACEE).

Prof. Paulo Batista, University of Évora, Portugal

Speech Title: Architectural Records: Dealing With Complexity

Abstract: Personal archives of architects pose countless problems and challenges to the information services where they are located or to those preparing to receive them: among others, large volume, easily reaching tens of thousands of documents, fragility of the supports and numerous formats, many of which are large dimension, with profound consequences in terms of its organization, classification, description, conservation, preservation, access, and dissemination. Involving this dynamic, its treatment implies the allocation of, at least, one collaborator for a considerable period, in addition to the fact that its target audience is residual, which normally seeks this documentation as part of research project, especially master's dissertations and doctoral theses. Considering this reality, what strategies should be implemented to face these problems and challenges, transforming them into opportunities?

Biography: Paulo Batista is PhD Researcher at CIDEHUS.UÉ-Interdisciplinary Center for History, Cultures and Societies of the University of Évora, Portugal, where is the coordinator of the research group 2: Heritage and Literacies. Currently works as a higher technician in the Municipal Archives of Lisbon, and professor at the Autonomous University of Lisbon, where is coordinator and professor of the Postgraduate in Promotion and Cultural and Educational Dynamization of Archives and Libraries, and the Postgraduate in Architectural Archives.

He has lectured in the MS program in Information Science and Documentation at Universidade NOVA de Lisboa and has held senior technician positions at the Portuguese Institute of Cultural Heritage, the Portuguese Institute of Architectural Heritage, and the Torre do Tombo Archives. He has also worked as researcher at the Center for the Study of History and Ancient Cartography of the Institute of Tropical Scientific Research.

Paulo Batista holds a Ph.D. in Documentation (University of Alcalá, Madrid-UAH), an MS in Information Science and Documentation - Archival Studies (UNL), and an MA in Documentation (UAH). As part of his doctorate, he also received a Diploma of Advanced Studies in Bibliography and Documentation Retrospective in Humanities (UAH), and he also holds a postgraduate degree in Information Society Law (University of Lisbon) and Information and Documentation Science - Librarianship and Archival Studies (UNL), and a specialization in Good Practices in Patrimonial Management (UNL) and Information Science and Documentation - Archival Studies (UNL). He holds an undergraduate degree in History (University of Lisbon).

Paulo Batista is the author of several books and about 90 papers published in international journals and conference proceedings. He was also keynote speaker and invited speaker at various international conferences (Portugal, Argentina, Belgium, Brazil, China, Ecuador, Egypt, England, Fiji, France, India, South Africa, Thailand, Türkiye and South Korea).

More information: https://www.cienciavitae.pt//0618-CE7B-7145

Assoc. Prof. Na Li, Beijing University of Posts and Telecommunications, China

Biography: Na Li is currently an associate professor of Beijing University of Posts and Telecommunications (BUPT). She serves as the deputy director of the mobile network security institute of the national engineering research center for mobile network technologies since 2021. She received the B.S. and M.S. degrees from the Ocean University of China, Qingdao, China, in 2009 and 2012, respectively, and the Ph.D. degree from the BUPT, Beijing, China, in 2015.
Her research interests are in the area of 5G-A/6G wireless communications and networks, with current emphasis on wireless security and privacy in integrated sensing and communications (ISAC), RIS assisted wireless networking, and resource allocation in integrated network of air, space and ground wireless networks. She has published 100 papers, patents, books and chapters of books, with one ESI highly cited paper. She received two science and technology awards issued by Chinese Institute of Electronics and Chinese Institute of Communications, and four best paper awards of international conferences.

Assoc. Prof. Shiying Han, Nankai University, China

Speech Title: Boosting Symbiotic Radio Networks Using Reconfigurable Intelligent Surface

Abstract: Enabled by ambient backscatter communication (AmBC) technique, symbiotic radio network (SRN) can provide internet-of-things (IoT) services with ultra-low power and spectrum consumption. Compared with long range radio (LoRa) and narrow-band IoT (NB-IoT) which respectively operate in unlicensed ISM band and LTE band, the backscatter transmission suffers from double fading and path loss which severely restrict its service range. In this talk, we will present our recent works that aim to release this bottleneck by employing the newly emerging reconfigurable intelligent surface (RIS) techniques, including the traditional single-layer RIS, simultaneously transmission and reflection RIS (STAR-RIS), and reconfigurable holographic surface (RHS). Related wireless resource and beamforming optimization problems and solving algorithms will be elaborated. Finally, promising tendency of SRN application enabled by RIS will be discussed.

Biography: Dr Shiying Han (Member, IEEE) received the B.Eng. degree in communication engineering from Tianjin University, Tianjin, China, in 2008, the M.Eng. degree in communication and information system from the Beijing University of Posts and Telecommunications, Beijing, China, in 2011, and the Ph.D. degree in electrical and electronic engineering from Nanyang Technological University, Singapore, in 2015. She was a Research Fellow with NTUSinBerBEST, Singapore. She is an Associate Professor and serve as the Assistant of Dean in the College of Electronic Information and Optics Engineering, Nankai University. Her current research interests focus on the intelligent spectrum sharing in heterogeneous networks, symbiotic radio networks, ultra-lower-power wireless transmission.

Assoc. Prof. Yang Yang, Shandong University, China

Biography: Yang Yang is an Associate Professor and Doctoral Supervisor in the School of Information Science and Engineering at Shandong University. Holding a Ph.D. from Shandong University (2009) and postdoctoral expertise in biomedical engineering (Imperial College London), he specializes in signal processing, AI-driven pattern recognition, and cross-disciplinary applications such as big data analytics, embedded systems, and real-time signal detection. As the principal investigator of several key projects, he leads the National Key R&D Program initiative "Fast Signal Detection and Intelligent Recognition Algorithm Development" (2021–present). His research also addresses societal challenges through projects such as Intelligent Decision-Making Technology for Parole Supervision Based on Social State Monitoring Big Data (2018–2021) and Psychological Behavior Prediction and Risk Early-Warning Technologies (2021–2023). With over 40 publications in journals and conferences, 20+ Chinese invention patents, and 2 U.S. patents.

Assoc. Prof. Xiaoxuan Wang, Beijing Jiaotong University, China

Speech Title: Enhancing Task Offloading in IoV with a Two-Stage Algorithm under Information Asymmetry

Abstract: In the Internet of Vehicles (IoV), efficient task offloading is critical for overcoming vehicle resource constraints and meeting the demands of computationally intensive services. However, information asymmetry between vehicles and infrastructure poses significant challenges to optimal task offloading. We introduce a novel two-stage offloading strategy that combines Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC) algorithms to address these challenges. The first stage employs PPO to decide whether tasks should be offloaded to Roadside Units (RSUs) based on task urgency and system status, while the second stage uses SAC to optimize partial offloading decisions, including task distribution among service vehicles and incentive mechanisms. Simulation results demonstrate that this approach effectively reduces task urgency in the buffer queue and enhances overall system efficiency and reliability compared to traditional methods. The proposed strategy provides a robust solution for task offloading in IoV scenarios characterized by information asymmetry and vehicle selfishness.

Biography: Dr. Xiaoxuan Wang received his Ph.D. degree in traffic control and information engineering from Beijing Jiaotong University, Beijing, China, in 2020. From 2017 to 2018, he was a Visiting Scholar with Dr. Lingjia Liu in Wireless@VT, Virginia Tech, VA, USA. He is currently an Associate Professor at the School of Electronic and Information Engineering, Beijing Jiaotong University, and the Associate Director at the Cyber-Physical Systems & Industrial Software Lab. His main research interests are in dependability and security for wireless communications and communication networks in smart city, intelligent transportation and railway transportation. He has published more than 30 research papers in top international conferences and journals, such as IEEE T-ITS, T-VT, IoT-J, IET-ITS, ICC, WCNC, Globecom, VTC, etc. He has been the recipients of the 2018 International Conference on Intelligent Rail Transportation Best Paper Award.

Assoc. Prof. Syed Mushhad Mustuzhar Gilani, University of Agriculture, Pakistan

Biography: Dr. Syed Mushhad Mustuzhar Gilani is an Associate Professor in the Department of Computer Science at the University of Agriculture, Faisalabad, Pakistan. He also serves as an Associate Senior Tutor, Postgraduate Research Advisor, and Convener of multiple institutional committees.
Previously, Dr. Gilani was an Assistant Professor in Computer Science and a Postgraduate Research Advisor at PMAS-Arid Agriculture University, Rawalpindi, where he contributed significantly to academic excellence from 2012 to 2022.
Dr. Gilani earned his Ph.D. from the School of Computer Science, Chongqing University of Posts and Telecommunications, China. With a prolific academic and research career, he has authored over 60 publications in esteemed international journals and conferences. His expertise extends to successfully supervising postgraduate research projects and actively participating in the academic community as a session chair and invited speaker for prestigious conferences and a reviewer for high-impact journals.
Dr. Gilani's achievements include receiving the "Excellent Speaker Award" at the TEDx Youth Festival 2017 hosted by Chongqing University of Posts and Telecommunications, China.
His research interests encompass cutting-edge areas such as Future Internet Architectures, Software-Defined Wireless Networks, the Internet of Things (IoT), and Smart Environments.

Assoc. Prof. Bitao Pan, Beijing University of Posts and Telecommunications, China

Biography: Dr. Bitao Pan is currently an associate professor at Beijing University of Posts and Telecommunications. His research interests include design and modelling of optical networks, software defined automatic optical networking, FPGA based fast optical switching, and optical interconnects in distributed machine learning. Dr. Bitao Pan obtained his PhD degree from ECO group of Eindhoven University of Technology, The Netherlands, under the supervision of Dr. Nicola Calabretta and Prof. Ton Koonen. During his PhD, Bitao Pan has attended in 3 European H2020 research projects, the Metro-Haul, PASSION, and Qameleon. He has (co)authored more than 30 research papers, which include IEEE/Optica JOCN, IEEE/Optica JLT, IEEE TCOM, et.al. His is also serving as reviewers to IEEE/Optica JOCN, IEEE JSAC, Nature LAS, et.al.

Assoc. Prof. Yingyang Chen, Jinan University, China

Speech Title: URLLC Design for Autonomous Driving: A Rate-Splitting Finite Blocklength Approach

Abstract: Autonomous driving demands ultra-reliable and low-latency communication (URLLC) to ensure safe and efficient operation in highly dynamic environments. This talk introduces a novel communication framework that combines rate-splitting multiple access (RSMA) with finite blocklength (FBL) design to meet these demanding requirements. We develop closed-form solutions and jointly optimize power allocation and rate splitting, considering real-world factors and changing channel conditions. This approach improves reliability and fairness, showing strong robustness in high-mobility scenarios, and effectively supports the critical communication needs of autonomous driving systems.

Biography: Dr. Chen is an Associate Professor at Jinan University. She received her B.Eng. from Yingcai Honors College, University of Electronic Science and Technology of China, and her Ph.D. from Peking University. She was a visiting student at the University of Southampton in 2018. Her research interests include next-generation multiple access, cross-layer resource allocation, and aerial intelligent networks. Dr. Chen has received the Fund for Distinguished Young Scholars of Guangdong Province and the First Prize of the Science and Technology Progress Award from the China Work Safety Association. She is an Editor for IEEE Communications Letters and a Senior Member of IEEE.

Assoc. Prof. Liwei Yang, China Agricultural University, China

Biography: Dr. Liwei Yang, associate professor of China Agricultural University. She received the B.E. degree in Telecommunication Engineering from Chongqing University of Posts and Telecommunications, China, and the Ph.D. degree in Information and Communications Engineering from Beijing University of Posts and Telecommunications, China. From 2009 to 2011, she was a Postdoctoral Research Fellow with the Department of Electronic Engineering, Tsinghua University, China. In 2015, she joined the faculty of the College of Information and Electrical Engineering, China Agricultural University. Her research interests include optical networks, optical wireless communications and visible light communication. She participated in a number of national projects and published more than 100 papers. She served as a TPC member of several international academic conferences and a reviewer for several international journals.

Assoc. Prof. Jiazhi Ma, National University of Defense Technology, China

Speech Title: Multi-domain Approach against Complex Active Jamming

Abstract: Active jamming countermeasures have emerged as a critical challenge in the radar field. Effective anti-jamming approaches serve as the foundational prerequisite for radar detection and perception in the battlefield complex electromagnetic environment. This presentation first outlines the complex active jamming threats for radars, then presents several novel multi-domain anti-active jamming methods. By implementing flexible processing across the multi-domain of time frequency space and polarization, these anti-jamming methods based on waveform, beamforming, and signal features achieve good performance in mitigating some new active jamming patterns.

Biography: Ma Jiazhi is currently an associate professor and master's supervisor at the College of Electronic Science, National University of Defense Technology. He received the M.S. degree in 2012 and Ph.D. degree in 2017. His research interests include radar signal processing and radar polarization anti-interference.

Senior Engineer Dr. Dongdong Wang, 54th Research Institute of China Electronics Technology Group Corporation, China

Biography: Dongdong Wang received the Ph.D. degree in Information and Communication Engineering from the Beijing University of Posts and Telecommunications (BUPT), in 2018. He currently holds the professional title of Senior Engineer, serves as a Master's supervisor at China Electronics Technology Group Corporation, and has been appointed as an Institute-level Expert in the field of LEO satellite transmission technology at the 54th Research Institute of China Electronics Technology Group Corporation. He has authored or coauthored over 30 technical articles in international journals and conferences. His research interests include information theory and channel coding, 5G based LEO satellite transmission technology.

Lecturer Kaitao Meng, University of Manchester, UK

Speech Title: Integrated Sensing and Communication Networks: Design, Analysis, and Optimization

Abstract: Network-level Integrated Sensing and Communication (ISAC) unifies target sensing and data transmission across multiple base stations, treating them as intertwined services over the same hardware, spectrum, and backhaul. By coordinating beamforming, waveform design, and resource allocation at the network scale, it expands coverage and spatial resolution, introduces extra degrees of freedom for balancing sensing accuracy against throughput, and leverages shared spectrum and hardware to boost spectral and energy efficiency. This webinar will provide an overview of network-level ISAC and explore multi-layer collaboration schemes, covering interference suppression, cooperative signal processing, and network-wide resource allocation, highlighting both the performance gains achieved and the costs incurred. Centralized or distributed coordination further mitigates interference and enhances robustness, while cooperative architectures ensure scalability and resilience under dynamic topologies. As a fully coordinated service, network-level ISAC unlocks multifunctional 6G capabilities, high-precision localization, real-time environment mapping, and ultra-reliable communications, across smart cities, industrial sites, and beyond.

Biography: Kaitao Meng received the B.E. and the Ph.D. degrees from the School of Electronic Information, Wuhan University, Wuhan, China, in 2016 and 2021, respectively. From 2021 to 2023, he was a Postdoctoral Researcher in the State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China. From 2023 to 2025, he worked as a Marie Curie Fellow with the Department of Electronic and Electrical Engineering, University College London, U.K. Starting in August 2025, he will join the Department of Electrical and Electronic Engineering at the University of Manchester as a Lecturer (Assistant Professor). His current research interests mainly include integrated sensing and communication, cooperative sensing, network-level ISAC, and intelligent surfaces.
He was the recipient of the 2022 EU Marie Curie Postdoctoral Fellowship. He is a Guest Editor for IEEE TCCN and Journal of radars, Associate Editor for IEEE IoT. He has also chaired several IEEE conference tracks and workshops, including Track Co-Chair of IEEE VTC-Spring 2025 and Co-Chair roles at IEEE ICC Workshop 2025, IEEE GlobeCom Workshop 2024-2025, WiOpt Workshop 2025 on Integrated Sensing and Communications.

Dr. Kai Li, CISTER Research Unit at ISEP/IPP, Portugal

Biography: Kai Li is a Visiting Research Scholar with the School of Electrical Engineering and Computer Science, TU Berlin, Germany, and a Senior Research Scientist with the CISTER Research Centre, Porto, Portugal. He is also a CMU-Portugal Research Fellow, jointly supported by Carnegie Mellon University (CMU), Pittsburgh, PA, USA, and the Foundation for Science and Technology (FCT), Lisbon, Portugal. From 2023 to 2024, he was a Visiting Research Scientist with the Division of Electrical Engineering, Department of Engineering, University of Cambridge, UK. In 2022, he was a Visiting Research Scholar with the CyLab Security and Privacy Institute, CMU. Prior to this, he was a Post-Doctoral Research Fellow with the SUTD-MIT International Design Centre, Singapore University of Technology and Design, Singapore, from 2014 to 2016. He has also held positions as a Visiting Research Assistant with the ICT Centre, CSIRO, Brisbane, QLD, Australia, from 2012 to 2013, and a full-time Research Assistant with the Mobile Technologies Centre, The Chinese University of Hong Kong, Hong Kong, from 2010 to 2011. He received the Ph.D. degree in computer science from The University of New South Wales, Sydney, NSW, Australia, in 2014, the M.S. degree from The Hong Kong University of Science and Technology, Hong Kong, in 2010, and the B.E. degree from Shandong University, China, in 2009. He has been an Associate Editor of journals, such as Internet of Things (Elsevier) since 2024, Nature Computer Science (Springer) since 2023, Computer Communications (Elsevier) and Ad Hoc Networks (Elsevier) since 2021, and IEEE ACCESS from 2018 to 2024.

Dr. Zichao Li, Canoakbit Alliance / University of Waterloo, Canada

Speech Title: Lightweight Adversarial Training for Secure IoT Communication Applications

Abstract: The rapid proliferation of IoT devices in communication networks has introduced significant security challenges, particularly from evolving malware designed to exploit vulnerabilities in network protocols and edge software. Traditional malware detection methods struggle to adapt to these dynamic threats, especially in resource-constrained IoT environments where computational efficiency is critical. We present Lightweight Adversarial Training for Secure IoT Communication Software (LATICS), a robust deep learning framework designed to detect malware in IoT network traffic while resisting adversarial evasion attacks. By integrating MobileNet-based feature extraction, attention mechanisms, and Fast Gradient Sign Method (FGSM) adversarial training, LATICS achieves high accuracy in identifying malicious traffic patterns with minimal computational overhead.
Our approach specifically targets communication software vulnerabilities, including protocol impersonation (e.g., malicious MQTT/CoAP packets) and adversarial perturbations designed to bypass traditional intrusion detection systems. We evaluate LATICS on the CIC-IoT-2023 and TON-IoT datasets, which capture diverse network-level attacks (DDoS, ransomware, and spoofing). Experimental results demonstrate that LATICS achieves 99.2% detection accuracy—outperforming both signature-based tools (Snort) and ML-based NIDS (Kitsune)—while maintaining a 10× reduction in inference latency compared to cloud-centric solutions. The adversarial training pipeline enhances robustness, reducing the success rate of evasion attacks by 74% compared to non-hardened models.
A key innovation lies in LATICS’s edge-compatible design, enabling deployment on low-power devices (e.g., Raspberry Pi) without compromising detection fidelity. We further validate its practicality through integration with SDN controllers, showcasing real-time malware blocking in software-defined IoT networks. This work bridges the gap between adversarial machine learning and communication software security, offering a deployable solution for 5G/6G edge networks. Our findings highlight the critical role of lightweight, adversarially robust models in safeguarding the future of IoT communication ecosystems.

Biography: Dr. Zichao Li is currently a researcher at University of Waterloo. He holds PhD in management science. He is currently conducting research on machine learning optimization algorithms. I leverage on traditional optimization techniques used in transportation model to improve deep learning's knowledge graph structures. The main application area of his research is in financial market fraud and sentiment detection. His research interests are Pattern recognition for medical engineering; Big data and deep learning; Graph Convolutional Network; Neural Networks; Optimization Algorithms for big data; Reinforced Learning and Adversarial Learning; Self Supervised and Unsupervised Learning; Bayesian Optimization; RNN, LSTM, GNN; Knowlege-Graph Embedding; Explainable AI; Distributed Statistical Model. He also work as chief scientist at a fintech firm.

Invited Speakers of ICCSN2024


Prof. Pascal Lorenz, University of Haute-Alsace, France	Prof. Abdellatif KOBBANE, Mohammed V University in Rabat, Morocco	Prof. Gang Wang, Ningbo University, China (IEEE Senior Member)

Prof. Yuanguo Bi, Northeastern University, China	Assoc. Prof. Hongyan Fu, Tsinghua University, China	Assoc. Prof. Liwei Yang, China Agricultural University, China

Assoc. Prof. Tian Pan, Beijing University of Posts and Telecommunications, China	Assoc. Prof. Xiaoxuan Wang, Beijing Jiaotong University, China	Assoc. Prof. Hoshang Kolivand, Liverpool John Moores University, UK (IEEE Senior Member)

Assoc. Prof. Chao Fang, Beijing University of Technology, China (IEEE Senior Member)	Assoc. Prof. Dawei Wang, Sun Yat-sen University, China	Assoc. Prof. Mengwei Xu, Beijing University of Posts and Telecommunications, China

Senior Engineer Dr. Dongdong Wang, Network Communication Research Institute of China Electronics Technology Group Corporation, China	Dr. Yanan Liang, Beijing Jiaotong University, China	Dr. Amjad Ali Amjad, Zhejiang University, China