Prof. Jiangzhou Wang
International Member of the Chinese Academy of Engineering (CAE)
Fellow of the Royal Academy of Engineering (RAEng), U.K.
Fellow of IEEE, Fellow of IET

Southeast University, China

Speech Title: Target Localization in Cooperative ISAC Systems

Abstract: The integration of sensing capabilities into communication systems, by sharing physical resources, has a significant potential for reducing spectrum, hardware, and energy costs while inspiring innovative applications. Cooperative networks, in particular, are expected to enhance sensing services by enlarging the coverage area and enriching sensing measurements, thus improving the service availability and accuracy. This talk presents and discusses a cooperative integrated sensing and communication (ISAC) framework by leveraging information-bearing orthogonal frequency division multiplexing (OFDM) signals transmitted by access points (APs).

Biography: Jiangzhou Wang is a Professor at Southeast University, China, and Emeritus Professor at the University of Kent, U.K. He has published more than 500 papers and five books. His research interest is in mobile communications. He was a recipient of the 2024 IEEE Communications Society Fred W. Ellersick Prize and the 2022 IEEE Communications Society Leonard G. Abraham Prize. He was the Technical Program Chair of the 2019 IEEE International Conference on Communications (ICC2019), Shanghai, Executive Chair of the IEEE ICC2015, London, and Technical Program Chair of the IEEE WCNC2013. Professor Wang is an International Member of the Chinese Academy of Engineering (CAE), a Fellow of the Royal Academy of Engineering (RAEng), U.K., Fellow of the IEEE, and Fellow of the IET.

 

Prof. Min Chen
Fellow of IEEE, Fellow of IET, Fellow of AAIA
Highly Cited Researcher (2018-2024)

South China University of Technology, China

Speech Title: Large Language Model (LLM) Fine Tuning: Concepts, Opportunities, and Challenges

Abstract: As a foundation of Large Language Models, fine-tuning drives rapid progress, broad applicability, and profound impacts on human-AI collaboration, surpassing earlier technological advancements. This talk examines the core principles, development, and applications of fine-tuning techniques, emphasizing its growing significance across diverse field and industries. By analyzing the latest round of LLM fine-tuning advancements, this talk explores potential future directions for the co-evolution of humans and AI, as well as emphasizing their potential to achieve higher levels of cognitive and operational intelligence. Specifically, this talk introduces Natural Language Fine-Tuning (NLFT). The pioneering work of NLFT is the first superior technique for paving the way to deploy various innovative LLM fine-tuning applications when resources are limited at network edges.

Biography: Min Chen is a tenured full professor in School of Computer Science and Engineering at South China University of Technology. He was the director of Embedded and Pervasive Computing (EPIC) Lab at Huazhong University of Science and Technology. He is the founding Chair of IEEE Computer Society Special Technical Communities on Big Data. He was an assistant professor in School of Computer Science and Engineering at Seoul National University. He worked as a Post-Doctoral Fellow in Department of Electrical and Computer Engineering at University of British Columbia from 2006 to 2009. He received Best Paper Award from IEEE ICC 2012 and IEEE IWCMC 2016, etc. He serves as associate editor for IEEE Transactions on Big Data, and ACM Transactions on Multimedia Computing, Communications, and Applications, etc. He was a Series Editor for IEEE Journal on Selected Areas in Communications. He was General Chair of CEI 2024, Symposium Chair of IEEE Globecom 2022 eHealth, Co-Chair of IEEE ICC 2012-Communications Theory Symposium, and Co-Chair of IEEE ICC 2013-Wireless Networks Symposium. He was General Co-Chair for IEEE CIT-2012, Tridentcom 2014, Mobimedia 2015, and Tridentcom 2017. He was keynote speaker for IEEE BHI-BSN 2022. He has 200+ SCI papers, including IEEE JSAC, IEEE TNNLS, IEEE TPDS, IEEE TWC, IEEE TSC, INFOCOM, AAAI, CVPR, Science, Advanced Materials, Nature Communications, etc. He has published 12 books, including Big Data Analytics for Cloud/IoT and Cognitive Computing (2017) with Wiley. His Google Scholar Citations reached 49,700+ with an H-index of 101. His top paper was cited 5,170+ times. He was selected as ESI Highly Cited Researcher from 2018 to 2024. He got IEEE Communications Society Fred W. Ellersick Prize in 2017, the IEEE Jack Neubauer Memorial Award in 2019, and IEEE ComSoc APB Oustanding Paper Award in 2022. His research focuses on cognitive computing, 5G Networks, wearable computing, big data analytics, robotics, emotion detection, mobile edge computing, LLM and fabric computing etc. He is an IEEE Fellow since 2021.

 

Prof. Chow-Yen-Desmond Sim
IEEE Fellow, IEEE AP-S Distinguished Lecturer (2024-2026)

Feng Chia University, Taiwan, China

Speech Title: Antenna Solutions and Analysis for Commercial 5G mmWave Antenna-in-Package (AiP) Designs

Abstract: This presentation will explore the latest trends in 5G millimeter-wave (mmWave) antennas and address the challenges encountered by engineers in this field. To enhance the audience's understanding of mmWave array antenna design within the framework of commercial Antenna-in-Package (AiP) systems, we will examine a series of commercial mmWave AiP designs, starting with the QTM 052. The discussion will explore the design techniques adopted in these solutions and compare them with recent developments in academic research. Finally, the presentation will conclude with a brief outlook on future 5G mmWave (FR2) and 6G communication.

Biography: Prof. SIM Chow-Yen-Desmond, born in Singapore in February 1971, received his B.S. degree in Electrical and Electronic Engineering from the University of Leicester, UK, in 1998, and his Ph.D. in the Radio System Group from the same university in 2003. He joined Feng Chia University in July 2003, where he has served as a Distinguished Professor since August 2016. Prof. Sim’s research interests focus on small antenna designs and RFID applications, particularly in 5G sub-6GHz/mmWave antennas, RFID antennas, antenna arrays, and laptop antennas. He has published over 200 SCI-indexed journal papers on these topics. Prof. Sim was elected a Fellow of the Institution of Engineering and Technology (FIET) in February 2013. He served as an Associate Editor (AE) for IEEE Access (2015–2022) and IEEE Antennas and Wireless Propagation Letters (AWPL) (2017–2023). Currently, he is an AE for the IEEE Journal of RFID, IEEE Open Journal of Antennas and Propagation, and the International Journal of RF and Microwave Computer-Aided Engineering. Prof. Sim has contributed to numerous conferences as a General Chair, Co-Chair, Technical Program Committee (TPC) Chair, or TPC member. He has also been invited as a Keynote, Workshop/Tutorial Speaker and Invited Speaker in many international conferences. He served as the Chapter Chair of the IEEE Antennas and Propagation Society (AP-S), Taipei Chapter (2016–2017), and was the founding Chapter Chair of the IEEE Council of RFID, Taipei Chapter (2017–2020). Prof. Sim received the IEEE AP-S Outstanding Reviewer Award (Transactions on Antennas and Propagation) for eight consecutive years (2014–2021) and the Outstanding Associate Editor Award from IEEE AWPL in July 2018. He was appointed as a Distinguished Lecturer of the IEEE Antennas and Propagation Society for the term 2024–2026. In 2025, Prof. Sim was elevated to IEEE Fellow “for contributions to the practical design and application of high-isolation broadband antennas and arrays."

 

Prof. Qingsheng Zeng
IEEE Senior Member

Université du Québec an Outaouais, Canada

Speech Title: Millimeter Wave Signal Propagation in Indoor Environment and Underground Mine

Abstract: With a huge spectrum of 5–7 GHz allocated as an unlicensed band worldwide, the 60-GHz millimeter wave frequency range has become attractive for future indoor networking. Very high data rates can be reached (on the order of several Gbps) because of the large available spectrum. With low interference with neighboring networks due to the oxygen resonance around 60 GHz, it becomes feasible to control mining machinery and implement underground communications by using wireless sensors. Modelling 60 GHz millimeter wave signal propagation in indoor environment and underground mine is of vital importance for realizing the above goals. Most of published channel modeling studies in the 60 GHz still make efforts to evaluate the heuristic diffraction coefficients around corners for relaying the signal while denying surrounding deflecting obstacles (DOs) and considering them as noise sources. Few measurements of radio propagation in underground mines have been carried out for the MIMO-mmW systems, including the effect of miners’ activity. In this presentation, the importance of the presence of deflecting obstacles (DOs) for indoor wireless local area network (WLAN) applications in the 60 GHz band is evaluated, the propagation characteristics of a MIMO-mmW system within an underground mine environment is discussed, with the effect of miners’ activity being considered.

Biography: Prof. Qingsheng Zeng, received his Ph.D. from University of Ottawa, Canada, and is currently a professor and PhD advisor of Université du Québec an Outaouais (UQO), an adjunct professor and PhD advisor of University of Ottawa, Carleton University, and Institut National de la Recherche Scientifique -- Centre Energie, Matériaux et Télécommunications (INRS-EMT). He has been a research engineer and a senior research engineer at Communications Research Centre Canada (CRC), Government of Canada. Dr. Zeng has undertaken research and teaching in several fields, including analysis and design of aircraft antennas, electromagnetic compatibility and interference (EMC/EMI), ultrawideband technology, radio wave propagation, computational electromagnetics. He has been the Chair of AP (Antennas and Propagation) / MTT (Microwave Theory and Techniques) Joint Chapter and Secretary of EMC (Electromagnetic Compatibility) Chapter of IEEE Ottawa, a Member of IEEE Canada Industry Relations Committee, and a senior member of IEEE. Dr. Zeng has been a member of the Strategic Projects Grant (SPG) Selection Panel (Information and Communications Technologies B) for the Natural Sciences and Engineering Research Council of Canada (NSERC), a member of Site Visit Committee of NSERC Industrial Research Chair (IRC), and a reviewer of NSERC Industrial R&D Fellowships.
He has published more than 200 SCI and EI indexed papers and technical reports, authored one book and co-authored two book chapters. His work on the project “Aggregate Interference Analysis and Suitability of Some Propagation Models to Ultra-wideband Emissions in Outdoor Environments” has formed one part of Consultation Paper on the Introduction of Wireless Systems Using Ultra Wideband Technology, Spectrum Management and Telecommunications Policy, Industry Canada, and has been taken as a significant contribution to International Telecommunication Union (ITU). Dr. Zeng has been serving as an editorial board member and a reviewer for a number of technical books and scientific journals, as a conference co-chair, a session chair and organizer, a technical program committee co-chair and member and a reviewer, a short course/workshop/tutorial presenter and a keynote speaker for many international and national symposia. He has won several technical and technical service awards, was ranked as one of the researchers at Communications Research Centre Canada with the strongest impacts in 2011, selected as a distinguished expert under the Plan of Hundreds of Talents of Shanxi Province in China during 2015, a Huashan Mountain Scholar Chair Professor of Xidian University in 2020, and a distinguished expert for HOME Program of China Association for Science and Technology in January 2023, and was elected as a member of the Council of the Academicians and Experts Association of Jilin Province in December 2023.

 

 

INVITED SPEAKERS of WCCCT2025

 

Prof. Yonghua Li

Beijing University of Posts and Telecommunications, China

Speech Title: Improving Drilling Rate Prediction with Advanced Data Preprocessing and LSTM-Attention Mechanisms for Offshore Oil Drilling

Abstract: This study proposes a deep learning model combining Long Short-Term Memory (LSTM) and attention mechanisms for predicting drilling rate (ROP) in offshore oil drilling. The model processes time-series production data, extracts key features, and predicts future ROP with improved accuracy and real-time performance. Data preprocessing techniques, including outlier detection and duplicate removal, ensure high-quality data. The model outperforms traditional approaches such as LSTM, Temporal Convolutional Networks (TCN), and Gated Recurrent Units (GRU), achieving an RMSE of 0.154, MAE of 0.045, and an R² score of 0.908. This LSTM-Attention model offers strong support for real-time drilling optimization and can be further enhanced by integrating domain-specific knowledge and real-time data updates.

Biography: Yonghua Li is currently a professor, PHD supervisor with School of Information and Communication Engineering, Beijing University of Posts and Telecommunications. The main research interests are: Internet of Things, cloud computing and big data processing technology. He has 30 years of research and development experience in the key technical fields of Internet of Things, cloud computing and big data processing technology, undertaken more than 30 theoretical research and engineering projects, published more than 100 papers in academic journals and conferences and applied for 50 patents. More than 40 monographs and textbooks have been published.

 

Prof. Hao Zhang
Fellow of American Statistical Association, Elected Member of the International Statistical Institute

Michigan State University, USA

Speech Title: Kriging Through the Lens of Weighted Ridge Regression

Abstract: Kriging, the best linear unbiased prediction method, is widely applied in agriculture, geology, environmental and climate studies, and computer experiments. It shares deep connections with kernel learning methods in machine learning, where it is known as Gaussian process regression. Additionally, by the representer theorem, Kriging can be viewed as nonparametric smoothing in a functional space. In this talk, I will demonstrate how the Kriging solution can be obtained via weighted ridge regression, offering a new perspective that facilitates the use of existing ridge regression software. I will also discuss applications of this approach.

Biography: Hao Zhang is Professor and Chair at the Department of Statistics and Probability at Michigan State University. He is Fellow of American Statistical Association and an Elected Member of the International Statistical Institute. He has served editorial boards of Journal of the American Statistical Association, Statistica Sinica, Environmetrics, and Statistics & Probability Letters. His research interests are primarily in spatial and spatio-temporal statistics. His work includes both theoretical investigation into asymptotic properties of machine learning methods for spatial data and development of algorithms for the analysis of big spatial data. He collaborates with researchers in ecology, environmental sciences, climatology, and natural resources.

 

Prof. Kwok L. Chung
IEEE Senior Member

Guangzhou Institute of Science and Technology, China

Speech Title: Harmonizing Tradition and Innovation: Advances in Chinese-Culture-Based Antennas and Sensors

Abstract: This paper presents the innovative application of Chinese-culture-based (CCB) design in the development of multiband patch antennas, integrating culturally resonant symbols such as traditional motifs and calligraphic elements like Lishu characters. We trace the evolution of CCB antennas, highlighting advancements from the pioneering WANG-shaped patch antennas to the recent multiband Guo- and Qing-shaped designs. These antennas not only celebrate China's rich cultural heritage but also enhance performance and aesthetic value in wireless communication. Employing methodologies such as Characteristic Mode Theory (CMT), our research demonstrates how tradition can blend seamlessly with modern technology. The findings highlight the potential of CCB antennas for smart cities, cultural heritage sites, and sustainable practices, illustrating the convergence of art and technology in the field of wireless communications.

Biography: Kwok L. Chung received his Ph.D. degree in Electrical Engineering from the University of Technology Sydney, NSW, Australia, in 2004. Following his graduation, he joined the Faculty of Engineering at the University of Technology Sydney as a Lecturer. In 2006, he transitioned to The Hong Kong Polytechnic University, and in 2012, he became a member of the Institute for Infrastructure Engineering at the University of Western Sydney, Sydney, NSW, Australia. In 2015, he joined Qingdao University of Technology (QUT) in Qingdao, China, as a Research Professor, where he supervises Ph.D. students and leads a cross-disciplinary research team at the Civionics Research Laboratory. From April 2021 to July 2024, he served as a Research Professor at Huizhou University. Currently, he is a Research Professor at the Guangzhou Institute of Science and Technology (GZIST), China. Prof. Chung has authored and co-authored approximately 100 articles in SCI journals and over 120 conference papers indexed by EI since 2000, covering various fields within electrical engineering, computer science, and civil engineering. He served as the Vice Chair and then Chairman of the IEEE AP/MTT Hong Kong Joint Chapter in 2010 and 2011, respectively, and is also the Founding Chair of the IEEE Qingdao AP/MTT/COM Joint Chapter (CN10879) under the Beijing Section. His editorial contributions include serving as an Associate Editor for IEEE Access from 2016 to 2022 and for the Alexandria Engineering Journal since 2020.
Recognized for his significant contributions to scientific research, Prof. Chung was selected for the World’s Top 2% Scientists list published by Stanford University from 2019 to 2023. He was also the sole representative from GZIST included in the 2023 Career Long-Term Impact list, underscoring his remarkable position and influence in academia. His current research interests encompass wireless sensors, characterization of cement-based materials, WiFi-7, 5G/6G microwave and millimeter-wave antennas, artistic antennas, and MIMO antenna systems.

 

Prof. Botao Feng
IEEE Senior Member, Stanford University World's Top 2% Scientists, Head of Shenzhen University Key Laboratory of Wireless Communication, Antennas and Propagation

Shenzhen University, China

Speech Title: Multi-Function Multi-Beam Reflectarray Antenna for Sub-Terahertz Applications

Abstract: A single-layer-substrate dual-band multi-beam reflectarray antenna based on polarization selection technique for sub-terahertz (sub-THz) applications is proposed in this talk. The antenna element consists of two primary ring components (outer and inner) that are orthogonally nested to achieve dual-band characteristics. The outer component is a split ring structure aligned along the y-axis, designed to excite X-polarized radiation through a pair of arc-shaped phase shift lines extending from the sides of the ring. The inner component, located within the outer ring, comprises two small arc-shaped microstrip patches connected vertically by a straight-bar microstrip line, resulting in Y-polarized radiation. Furthermore, the digital coding metasurface together with the single- and multi- focus phase compensation techniques , enables the antenna array to achieve four-beam radiation and dual-beam scanning in the lower and upper frequency bands. Measured results show a very wide elevation angle of up to 104°and a high aperture efficiency of 49.2% at the lower frequency of 135 GHz. At the upper frequency of 170 GHz, a low scanning loss of 1.6 dB and a high aperture efficiency of 29% are realized. Additionally, high peak gains of 19.7 dBi and 26.3 dBi are obtained for the respective bands. Therefore, the proposed sub-THz reflectarray antenna presents itself as a promising candidate for future 6G point-to-multipoint communication systems, offering large capacity, wide coverage, and high-resolution scanning capabilities.

Biography: Botao Feng (Senior Member, IEEE) was born in Guangdong, China, in 1980. He received the B.S. and M.S. degrees from the Chongqing University of Posts and Telecommunications (CQUPT), Chongqing, China, in 2004 and 2009, respectively, and the Ph.D. degree from the Beijing University of Posts and Telecommunications (BUPT), Beijing, China, in 2015, all of which degrees are communication and information system majors. Dr. Feng joined Nokia Mobile Phones Ltd., Dongguan, China, as a Communication Engineer, in 2004. From 2009 to 2012, he served as a Senior Engineer and a Chief Executive in China United Network Communications Company Ltd., Guangzhou, China, where he won the Award of Breakout Star of the Year and the title of Technical Innovation Expert.

Dr. Feng currently acts as the Head, the Supervisors of graduate student and overseas doctoral student of the Shenzhen University Key Laboratory of Wireless Communication, Antennas and Propagation, which includes more than 70 research members and complete industry-university-research facilities in antenna and communication fields, and is a founding member of State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), and the President of Shenzhen Bodasheng/Taobida Technology Company Ltd., Shenzhen, China. In addition, he has been a Distinguished Senior Research Fellow with Energy Materials Telecommunications Research Centre, Institut National De La Recherche Scientifique (INRS), Quebec City, QC, Canada, since 2020, and a Distinguished Visiting Professor of Huizhou University, Huizhou, China, since 2022. His research interests include antennas and mobile communications. He and his research team members are currently conducting multiple projects on antenna development for advanced mobile communications, which are supported by natural science research funds and industrial cooperation research and development funds. His several antenna designs for 5G/WiFi applications have been widely used by Chinese communication operators. It is estimated that the related total production value is around 2 billion Ren Min Bi (RMB). He has authored or co-authored nearly 200 technical articles, including approximately 60 science citation index (SCI) and 180 engineering index (EI) articles in which approximately a third of them are reported in top journals, and holds more than 80 technical patents. In the past few years, he has obtained the award of the Outstanding Instructor of the First Prize in the National Graduate Electronic Contest and the Tencent Outstanding Teacher Award. Since 2021, he has been a successive recipient of ''Stanford University World's Top 2% Scientists''.

Dr. Feng is a Senior Member of the IEEE Antennas and Propagation Society and the IEEE Vehicular Technology Society. He serves as a Regular Peer Reviewer, a Technical Program Committee Chair, a General Chair, and an Editor of IEEE/IET, Elsevier, Wiley, and Springer journals and conferences on microwave technique and antenna development. In addition, he concurrently also acts as a Senior Expert of Degree and Graduate Education Center of the Chinese Ministry of Education, Natural Science Foundation Committee of Guangdong Province/Zhejiang Province, Digital Government Expert Resource Pool of Guangdong Province, Information and Communication Technologies Senior Title Evaluation Committee of Guangdong Province, University Achievement Transformation Center of Guangdong Province, Electronic Communication Senior Title Evaluation Committee of Shenzhen City, Science and Technology Expert Database of Shenzhen City, Science and Technology Innovation Bureau of Shenzhen City, and Industry and Information Technology Bureau of Shenzhen City, etc..

 

Prof. Yindong Xiao

University of Electronic Science and Technology of China, China

Biography: Xiao Yindong, a professor at the University of Electronic Science and Technology, has been at the forefront of integrated circuit (IC) testing system research, contributing innovative methods for test vector synthesis instruction design, optimization of complex vector synthesis scheduling, and enhancement of simulation and RF IC testing algorithms. These advancements have notably improved key performance indicators, including vector synthesis rate, test signal quality, and single-chip testing efficiency. As the principal investigator of 8 national projects, including 3 key initiatives and a National Natural Science Foundation grant, Professor Xiao has published over 20 academic papers, with more than 10 indexed in the SCI. He is a respected reviewer for the esteemed journal "ISA Transactions" and holds a US patent and 25 Chinese patents. His groundbreaking work has earned him the first prize from the Ministry of Education for Technical Invention. His development of a state-of-the-art, fully proprietary IC testing system has set a new benchmark in the industry, providing a comprehensive alternative to high-end testing instruments and meeting the urgent testing demands of chip development and production facilities. As a key contributor to the SpinalHDL agile digital design development library, Professor Xiao is pioneering research into next-generation hardware-software integrated HDL languages and their applications, further advancing the field of IC testing and design.

 

Prof. Xingquan Wang

Gannan Normal University, China

Speech Title: A Half-Bridge IGBT Drive & Protection Circuit for Inverter Power Supply

Abstract: The common IGBT drive and protection circuits are complex and expensive. Moreover, the circuit’s interfaces and the parameters are difficult to change. We designed a half-bridge IGBT drive and protection circuit with discrete components. It was easy to change the frequency, the duty cycle and the driving voltage and current of driving square wave signal which was then isolated into two outputs by using photoelectric coupler. The protection circuit was formed by using Hall sensor for direct detection of main circuit current with a minute amount of elements. Further, we build a high voltage power supply for DBD discharge whose output peak voltage can be changed continuously from 0 to 30 kV and frequency from 8 to 25 kHz with the output maximum power of 150 W.

Biography: Xingquan Wang was born in October 1980. He currently serves as the head of the Master's degree program in Electronic Science and Technology and as the chairman of the Physics Society of Ganzhou City. He received his Ph.D. degree in optics from Changchun University of Science and Technology in 2010. Following his graduation, he worked as postdoctor in the Institute of Physics, Chinese Academy of Sciences. In 2012, he became a teacher in Gannan Normal University. He visited Australia as a government-sponsored visiting scholar at Queensland University of Technology for one year in 2016. He engaged in fundamental research in low-temperature plasma discharge technology and electronic technology applications, publishing over 40 SCI/EI indexed papers and holding more than 30 authorized patents. He has led 8 teaching and research projects at or above the provincial level, including projects funded by the National Natural Science Foundation, and has been awarded the Jiangxi Provincial Natural Science Award.

 

 

Assoc. Prof. Hongyan Fu
IEEE Senior Member, Tenured-Associate Professor, Deputy Director of Research Office, Director of Nano-fabrication Platform, Tsinghua Shenzhen International Graduate School (SIGS)

Tsinghua University, Shenzhen, China

Speech Title: Spectral-Scanning FMCW LiDAR Based on Tunable VCSEL and Nonlinearity Correction Methods

Abstract: In recent years, light detection and ranging (LiDAR) has found widespread applications in fields such as autonomous driving, drones, mapping, and consumer electronics. Frequency-modulated continuous-wave (FMCW) LiDAR has gained significant attention from both academia and industry due to its superior performance compared to traditional approaches such as time-of-flight (ToF). In FMCW LiDAR systems, high speed and wide field-of-view (FoV) play a crucial role in determining imaging performance. The linearity of the laser frequency sweep is another key performance metric significantly affecting imaging resolution and precision. This talk will briefly review existing beam-steering methods and related work for ultrafast LiDAR systems, with a focus on the technological advancements of tunable vertical-cavity surface-emitting laser (VCSEL), nonlinearity correction methods, and spectral-scanning methods for FMCW LiDAR.

Biography: Dr. Fu is currently a tenured-associate professor, deputy director of Research Office, and director of Nano-fabrication Platform, Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, China. From 2010 to April 2017, Dr. Fu was a founding member and leading the advanced optic communications research at Central Research Institute, Huawei. His research interest focuses on integrated photonics and its related applications for communications and sensing, including optical wireless communication, LiDAR and silicon photonics, etc. He is a senior member of IEEE, Optica and life member of SPIE. He is the founding advisors of Optica/IEEE Photonics Society/SPIE Student Chapters at Tsinghua SIGS, Tsinghua University. He has authored/coauthored over 360 journal or conference papers, 3 book chapters, over 80 granted/pending China / US patents.

 

Assoc. Prof. Min Fu

Ocean University of China, China

Speech Title: Research on the Performance and Optimization Strategies of Underwater Wireless Optical Communication System under Microbubble Channel

Abstract: This research addresses critical challenges in Underwater Wireless Optical Communication (UWOC) systems within complex marine environments, focusing on two key aspects. Firstly, to mitigate the interference of micron-sized bubble swarms on communication performance, 10-250 μm bubble groups conforming to oceanic distributions were simulated via electrolysis, and their impact on Orthogonal Frequency Division Multiplexing (OFDM) links was quantitatively analyzed using an image acquisition platform. The results show that as bubble density increases, the bit error rate exceeds the Forward Error Correction (FEC) threshold. A 50mm large-aperture receiver improves the communication threshold by 136%, and combining Space-Time Block Coding (STBC) Multiple Input Multiple Output (MIMO) technology further enhances it by 50%. Secondly, to overcome the limited generalization capability of traditional channel modeling methods, a UWOC channel emulator based on Model-Agnostic Meta-Learning (MAML) and Deep Convolutional Conditional Generative Adversarial Network (DCGAN) is proposed. This emulator outperforms traditional methods in both time and frequency domains (time-domain correlation coefficient of 0.902, frequency-domain error reduced by 38%), demonstrating rapid adaptation to new water environments with varying attenuation coefficients. These findings provide effective solutions for performance optimization and channel modeling of UWOC systems in complex marine environments.

Biography: Dr. Min Fu is an Associate Professor at the School of Electronics Engineering, Ocean University of China. He obtained his Ph.D. in Electronic Science and Technology from Dalian University of Technology, complemented by a joint doctoral program at the University of Strasbourg in France. He has led over 15 national and provincial research projects, focusing on key areas such as marine technologies and underwater communication. His research achievements include publications in over 30 esteemed international journals, particularly in the fields of optical imaging and underwater communication. He has also secured 12 patents pertaining to related technologies. Dr. Fu is committed to advancing marine technology and education, evidenced by his awards, including first prizes from national organizations. He is also an active member of scholarly societies dedicated to instrumentation and sensor technologies.

 

Assoc. Prof. Qiang He

Northeastern University, China

Speech Title: UAV-assisted Microservice Mobile Edge Computing Architecture: Addressing Post-Disaster Emergency Medical Rescue

Abstract: In post-disaster emergency medical rescue operations, rapidly establishing an adaptive and flexible edge computing (EC) network, balancing data offloading with energy consumption, and ensuring the stable operation of the network have become urgent tasks. To address these challenges, we proposed a unmanned aerial vehicle (UAV)-assisted microservice mobile edge computing (MEC) architecture. The architecture can be rapidly deployed to provide temporary network coverage and EC services to disaster-stricken areas. A transformer-based resource management (TBRM) approach is utilized to optimize data offloading efficiency, and energy consumption, thereby maximizing the service time of the architecture. To ensure security and reliability, four microservices are designed to manage the full lifecycle of UAVs, utilizing dual digital signature certificates for identity authentication. Large-scale simulation experiments have demonstrated the effectiveness of the architecture in complex rescue environments, offering robust technical support for post-disaster medical rescue operations.

Biography: Qiang He received the Ph.D. degree in computer application technology from the Northeastern University, Shenyang, China in 2020. He also worked with School of Computer Science and Technology, Nanyang Technical University, Singapore as a visiting PhD researcher from 2018 to 2019. He is currently an Associated Professor at the College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China. His research interests include machine learning, social network analytic, data mining, health care, infectious diseases informatics, etc. He has published more than 70 journal articles and conference papers, including IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Cybernetics, IEEE Transactions on Cloud Computing, IEEE Transactions on Computational Social Systems, IEEE Transactions on Cognitive and Developmental Systems.

Qiang He is with the School of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China, e-mail: heqiang@bmie.neu.edu.cn

 

Assoc. Prof. Danyang Zheng (Personal Page)

Southwest Jiaotong University, China

Speech Title: A Cost-and-Time-Efficient Approach of Deploying Mixture of Expert Models

Abstract: The emerging large language models (LLMs) such as ChatGPT and DeepSeek have shown great potential in almost all fields. However, the current centralized cloud deployment fashion makes it barely possible to jointly serve tremendous user requests due to shortcomings like insufficient resources and high response delays. In response to relieving the above shortcomings, one approach is to deploy the LLM model in edge networks, which shortens the responding delay and lowers the volume pressure. This work shows the very pioneering efforts in deploying the mixture of expert models (MoE) LLM over edge networks. To begin, we formally formulate the MoE deployment problem. Next, we propose a novel cost-closeness centrality (CCC) measure and design the novel CCC-based router and aggregator deployment (3C-RAD) algorithm. Through extensive simulations, we have found that the 3C-RAD algorithm can significantly improve the runtime efficiency while keeping the cost efficiency in deploying MoE compared to brutal force.

Biography: Danyang Zheng, Ph.D., Associate Professor (since January 2023), Chief Technology Advisor at Sichuan Prologue Technology Co., Ltd., Youth Editorial Board Member of the journal Big Data Mining and Analysis (BDMA, IF: 13.6, 2023 latest Chinese Academy of Sciences ranking: Tier 1), IEEE member, CCF member. His research focuses on in-network computing, network reliability and security, and digital twins. He has published over 40 SCI/EI papers, including in top-tier journals and conferences such as IEEE INFOCOM, IEEE TDSC, IEEE TNSM, IEEE TCoM, IEEE IoTJ, Computer Networks, and BDMA, with over 20 as the first author or corresponding author. He is currently leading/working on multiple National Natural Science Foundation Youth Project, Sichuan Provincial Natural Science Foundation Youth Project, and horizontal research projects. He is serving as the Conference Publicity Chair of ICCC 2024 & WCCCT 2025, and has served as the Track Chair of WCCCT 2024, and program committee member for ICCC 2021-2024, IEEE ICTC 2023-2024, IEEE VTC 2023, and IEEE ICCT 2023.

 

Assoc. Prof. Chengzong Peng

Chengdu University of Information Technology, China

Speech Title: Distributed Pairwise Protection for Security-Aware Mission Chains in UAV Networks

Abstract: The unmanned aerial vehicles (UAVs) communication network exhibits significant potential in natural disaster management, with applications in flood relief and wildfire control. In these scenarios, UAVs can dynamically form mission chains (MCs) to collaboratively execute tasks such as real-time monitoring and post-disaster search and rescue. To address security challenges in these dynamic environments, we implement MCs as security-aware service function chains (SFCs). However, traditional SFC techniques are often inefficient and resource-intensive when applied to MCs in UAV networks, due to the networks' dynamic nature and resource constraints. In this paper, we introduce and mathematically formulate a novel problem, termed the security-aware SFC distributed pairwise protection (SSFC-DPP) problem in UAV networks, which optimizes SFC protection against failures while balancing security and resource demands, and prove its NP-hardness. To tackle SSFC-DPP, we propose an efficient heuristic approach, the distributed pairwise node protection (DPNP) algorithm, integrating a security-resource ratio (SRR) factor and pairwise backup selection (PBS) technique. Extensive simulations show that DPNP reduces overall backup costs by 8.05% and 51.39% compared to two benchmark algorithms, respectively.

Biography: Chengzong Peng, Ph.D., Associate professor, IEEE member, CCF member. His research focuses on network reliability, cyberspace security, artificial intelligence. He has published over 30 SCI/EI papers, including IEEE INFOCOM, IEEE TNSM, IEEE IoTJ, and Computer Networks. He is currently leading/working on multiple national and provincial-level scientific research projects. He is serving as the TPC of ICNC 2025, and has served as the Session Chair of WCCCT 2024, and the Talk Chair of ACM TURC 2024. He has also served as a reviewer for multiple well-known international academic journals and conferences, such as Big Data Mining and Analytics, Expert System with Applications, and Computer Network.

 

Assoc. Prof. Wei Yang

Shenzhen Technology University, China

Speech Title: Wi-Fi Signal Gesture Recognition Based on Multimodality

Abstract: With the development of technology, various gesture recognition devices and technologies have emerged to meet people's various needs. Traditional gesture recognition methods are relatively cumbersome and require wearing data gloves. At the same time, the technology based on computer vision needs to recognize that the target is always within sight. Therefore, we proposes a gesture recognition method based on multimodal Wi-Fi signals, and optimizes the gesture recognition methods from devices and technologies to overcome the problems in traditional recognition methods. Specifically, we first built a Wi-Fi signal data acquisition platform based on the Atheros network card, and the packet loss rate is less than 0.1%. Then, frame extraction is carried out for the video signal, and the T3D network based on DenseNet is used for video recognition. The video recognition rate reaches 95.0%. Finally, the above video data is extended to Wi-Fi signal, gesture recognition is performed jointly with CNN and GRU. The tests show that the gesture recognition rate of proposed scheme is 88.2%.

Biography: Wei Yang, Ph.D., Associate Professor of Engineering, IEEE Member. He received the Ph.D. degree in information and communication engineering from Beijing University of Posts and Telecommunications (BUPT), Beijing, China. He was also a Research Fellow with the State Key Laboratory of Networking and Switching Technology, BUPT, China. He has served as the TPC of ICCT (2021-2024), the Session Chair of WCCCT 2025, and also served as a reviewer for multiple well-known international academic journals and conferences. His research interests include wireless communication, cyber-physical system, information security and fusion.

 

Assoc. Prof. Bo Li

Ningxia University, China

Speech Title: Dual Power Supply Strategies for Ground-Air Integrated Network

Abstract: To address the issues of how to maximize renewable power utilization and lower the charging cost, power supply strategy for green base station and UAV is proposed in this speech. For base station, the strategy consists of Grid Connection Depth (GCD) model and Battery Power Sharing (BPS) model, which reduce the dependence on the grid and take advantage of idle power. The optimal power transfer variables are obtained to facilitate the strategy for maximizing renewable power utilization. For UAV, a static charging station strategy that exploits inductive coupling and battery hotswapping techniques is proposed. The strategy consists of nearby battery swapping strategy and charging station selection strategy for UAVs without time constraints (CTC). For describing the mutual competition among UAV charging selections in CTC strategy, a non-cooperative game framework with pure strategy is developed. An iterative algorithm is designed to solve the Nash equilibrium and obtain the optimal charging selection scheme. The optimal ratio of weighting factors is obtained through simulation and numerical analysis. Finally, the comparison results with other strategies indicate that the proposed strategies have the characteristics of low cost and low latency. The simulation results demonstrate that the proposed strategies have higher practical value compared with other power supply strategies.

Biography: Dr. Li is an associate professor in the School of Electronics and Electrical Engineering, Ningxia University, China. He received his Ph.D. degree in Information and Communication Engineering from Beijing University of Posts and Telecommunications (BUPT) in 2012. And he did Postdocal research from 2015 to 2017 at EEC, the University of Florida, USA. His main research interests include B5G/6G, Space-Air-Ground Integrated Network Architecture, Network Function Virtualization and Software Definition, Green Communication and Energy Efficiency, Integration of Communication and Energy networks, and Resource management for future communication. In recent years, he has published more than 30 papers in journals and conferences. He serves in several reviewer boards for several international conferences and journals. Dr. Li has served as the Chair of IEEE ICCT and ICCC.

 

Assoc. Prof. Dong Hou

University of Electronic Science and Technology of China, China

Speech Title: High-precision laser-based free space time and frequency transfer

Abstract: Laser-based free space time and frequency transfer is a new technique that involves transmitting time and frequency signals from one site to other site at a certain distance through free space, thereby achieving high-precision time-frequency synchronization between two or more sites. In the past few years, significant progress has been made in free space time and frequency transfer with the help of continuous laser and femtosecond laser. This presentation first introduces the basic principles of free space time and frequency transfer with laser, and then presents the latest research achievements in the field of free space time and frequency transfer, including free space time-frequency transfer based on continuous lasers, free space time-frequency transfer based on femtosecond optical frequency combs, and free space time-frequency transfer with weak signal based on single photon detection. Finally, some future development trends of free space time-frequency transfer are discussed.

Biography: Dong Hou was born in Sichuan, China, in 1982, and received the Ph.D. degree from Peking University, Beijing, in 2012. He was a Postdoctoral Fellow at Peking University, and University of Colorado Boulder, from 2012 to 2015. He was a Senior Visiting Scholar at Korea Advanced Institute of Science and Technology, South Korea, in 2015 and 2016. He is now an associate professor and doctoral supervisor of University of Electronic Science and Technology of China, Chengdu, China.
His current research interests include precise physical measurement, highly-stable time-frequency transfer over fiber and free-space link, timing jitter/phase noise measurement and stabilization of femtosecond laser. He participated in and completed a number of national 863, 973, and National Natural Science Foundation of China projects. He has been selected for municipal, provincial and ministerial talent programs, and published more than 60 journal papers. He has been invited to give oral presentations at international conferences for many times, and has applied for and authorized more than ten patents. Selected as an expert for the provincial and municipal overseas high-level talent program.

 

Associate Research Fellow Jie Tian

China Academy of Engineering Physics, Mianyang, China

Speech Title: Key Technologies for Secure Wireless Transmission Based on Covert Information Mapping and Spatial Direction Modulation

Abstract: We propose a comprehensive wireless secure transmission framework tailored for physical layer security communication, with a focus on key technologies integrating covert information mapping (CIM) and spatial direction modulation (SDM). First, to address the security degradation of traditional SDM systems when eavesdroppers are equipped with distributed receivers, we design the CIM-SDM structure, enhancing system robustness through covert information mapping. The detection performance of both legitimate users and eavesdroppers is theoretically derived, confirming the security advantages of this approach under extreme conditions. Second, we further introduce the CIM-GSDM system, which incorporates generalized spatial modulation (GSM), leveraging the indices of distributed receiver subsets and an interference matrix to modulate covert information. This effectively improves the bit error rate (BER) performance of legitimate users while significantly degrading the demodulation capability of eavesdroppers. Finally, we incorporate a joint precoding and artificial noise (AN) design to optimize system security, achieving dynamic optimization of multi-beam control and power allocation to maximize the secrecy rate. Simulation results demonstrate that the proposed framework significantly enhances the security of wireless transmission while maintaining the performance of legitimate users, making it well-suited for general physical layer secure wireless communication scenarios.

Biography: Jie Tian serves as the associate research fellow and master's supervisor in Institute of Electronic Engineering, China Academy of Engineering Physics, Mianyang, China. He received his B.S. and M.S. both from Chongqing University and Ph.D. from CAEP. He conducted advanced research at the University of Colorado Boulder as a visiting scholar (2014-2016). He serves as the Ph.D. engineering supervisor through joint key programs with the University of Electronic Science and Technology of China (UESTC) and Xidian University.

His current research interests mainly include robust telemetry system design and evaluation, precise channel measurement and estimation for wideband transmissions in combined space, physical-layer security, wireless network optimization and high-precision time-frequency synchronization. He has led and participated National-level and Provincial-level mandatory key projects and science foundations. His pioneering works in advanced communication systems design earned him the national military science and Technology Progress Awards (2nd Prize, 2014 and 3rd Prize, 2015) and Technological Innovation Awards (3rd Prize, 2018 and 2nd Prize, 2024) . He has published more than 30 papers, with highlights being an Editor’s Pick in Review of Scientific Instruments (2018) and a Top 5 Student Paper at IEEE Radar Conference 2016, and he has applied for and authorized 7 patents in secure transmission/novel communication waveform patterns. he serves as a expert reviewer for the National Natural Science Foundation, provincial-level major engineering/research projects and IEEE/OSA journals.

 

Assoc. Prof. Wenxing An

Tianjin University, China

Speech Title: Integrated Design of Photovoltaic Cells and Antennas

Abstract: With the proliferation of 5G communication systems, their energy consumption has significantly increased, leading to a substantial rise in the cost of communication systems. In response to these challenges, this report proposes an integrated design of photovoltaic power generation and wireless communication, aiming to realize dual functions of photovoltaic power generation and wireless communication by integrating photovoltaic cells with metal antennas. Dual-functional modules can be achieved by replacing the metal patches of traditional antennas with photovoltaic cells. This report will discuss the integrated design with broadband, lightweight, and dual polarization characteristics. The integrated photovoltaic communication design can reduce greenhouse gas emissions and environmental pollution, thereby promoting sustainable development in communication systems.

Biography: An Wenxing is an associate professor at Tianjin University. He has published over 40 journal articles in the fields of electronics and antennas, and has been granted over 20 Chinese patents and 2 US patents. His research focuses on the integrated design of solar cells and antennas for wireless communication and photovoltaic power generation. He has guided his students to win the Student Paper Award at the 2023 China Microwave and Millimeter Wave Conference for their work on ultra-wideband photovoltaic antennas for 5G. Additionally, he has developed an antenna array incorporating solar cells for spacecraft applications, with a solar cell coverage exceeding 80%.

 

Assoc. Prof. Youzhi Xiong

Sichuan Normal University, China

Speech Title: Energy-Efficient Transmission Techniques for 6G Mobile Communications

Abstract: Energy efficiency (EE) is a crucial KPI of future 6G mobile communications. At this point, this presentation will explore two enablers that are promising to improve the EE, i.e., low-resolution quantization and reconfigurable intelligent surface (RIS). Specifically, in the context of cell-free massive MIMO, a promising technology for 6G, we show how low-resolution quantization and RIS can improve system EE. Moreover, by involving the two enablers, we introduce some challenges to be investigated, such as performance analysis, channel estimation, and RIS’s configuration.

Biography: Youzhi Xiong received the B.E. degree in communication engineering from Henan University, Kaifeng, China, in 2011, and the M.E. and Ph.D. degrees in communication and information systems from the University of Electronic Science and Technology of China, Chengdu, China, in 2014 and 2019, respectively. He is currently an Associate Professor with the College of Physics and Electronic Engineering, Sichuan Normal University, Chengdu. His research interests include massive MIMO with low resolution ADCs and/or DACs, channel estimation, cell-free massive MIMO, machine learning, and reconfigurable intelligent surfaces. He has published over 20 SCI/EI papers, including IEEE TCOM, IEEE TVT, and IEEE IoTJ. He is currently leading/working on multiple national and provincial-level scientific research projects, including the National Natural Science Foundation of China and Sichuan Science and Technology Program. He has served as the Session Chair of WCCCT 2023& WCCCT 2024.

 

Assoc. Prof. Liwei Yang

China Agricultural University, China

Speech Title: Performance Analysis of Visible Light Communications (VLC)-WiFi Networks based on Dynamic Resource Allocation

Abstract: Visible Light Communications technology has become a potential solution for signal transmission in wireless optical network. In order to improve the fairness of the system, this study proposed an improved resource management algorithm for heterogeneous VLC-WiFi network. The simulation results show that the proposed algorithm has better fairness and throughput than the traditional algorithm.

Biography: 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. Feibo Jiang

Hunan Normal University, China

Speech Title: Large Model-Empowered Multimodal Semantic Communication

Abstract: Multimodal signals, including text, audio, image, and video, can be integrated into semantic communication systems to provide a low-latency, high-quality immersive experience at the semantic level. However, multimodal semantic communication faces several challenges, such as data heterogeneity, semantic ambiguity, and signal distortion during transmission.
In recent years, large models, particularly large language models (LLMs), vision-language models (VLMs), and large multimodal models (LMMs), have offered potential solutions to address these challenges. We conduct a systematic study on the application of large models in semantic communication, including a cross-modal semantic communication system based on VLMs, a multimodal semantic communication system empowered by LMMs, a multi-agent system leveraging LLMs, and a VLM-based multimodal, multi-user, and multi-task semantic communication system.
Additionally, we explore knowledge base design schemes based on large models and propose a foundational large model for the communication domain, enhanced with the retrieval-augmented generation (RAG) and knowledge graph. These methods will further enhance the performance of semantic communication, eliminate semantic noise, and provide valuable insights for the advancement of semantic communication technology.

Biography: Feibo Jiang received his B.S. and M.S. degrees in School of Physics and Electronics from Hunan Normal University, China, in 2004 and 2007, respectively. He received his Ph.D. degree in School of Geosciences and Info-physics from the Central South University, China, in 2014. He is currently an associate professor at the Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, China. His research interests include large AI model-assisted communications, machine learning, semantic communication, Internet of Things, and mobile edge computing.

Asst. Prof. Luping Xiang
Xiaomi Young Scholar

Nanjing University, China

Speech Title: Foundation Models for Communication and Sensing: A Paradigm Shift from Traditional Models to AI-driven Intelligence

Abstract: Deep learning (DL) is transforming communication and sensing, enhancing the intelligence of future 6G networks. To address challenges in generalization and transferability, this work introduces foundation models—modular architectures seamlessly integrating into communication and sensing systems. These models improve communication efficiency, enable cross-task parameter sharing, and significantly reduce sensing errors. Additionally, a novel pre-equalization strategy dynamically adapts transmitted signals using sensing information, mitigating channel impairments without modifying pre-trained models. Simulation results validate the effectiveness and transferability of foundation models, highlighting their potential to bridge model-driven and data-driven approaches in communication and sensing.

Biography: Luping Xiang (Member, IEEE) is an Assistant Professor, Research Fellow, and Ph.D. supervisor at Nanjing University. He received the B.Eng. degree (Hons.) from Xiamen University, China, in 2015, and the Ph.D. degree from the University of Southampton, in 2020. From 2020 to 2021, he was a Research Fellow with the Next Generation Wireless Group, University of Southampton. In November 2021, he joined the University of Electronic Science and Technology of China (UESTC) as a faculty member, and in September 2024, he joined Nanjing University as an Assistant Professor.

In 2024, he was honored with the Xiaomi Young Scholar Award, he also co-founded the company Accelercomm. He is currently leading several projects, including the National Natural Science Foundation of China's Youth Project, Provincial Youth Science Foundation, and the Special Funding Project at the Postdoctoral research. He has also received funding from the Postdoctoral International Exchange Program and has participated in multiple national key projects. He currently serves as an associate editor for the journal IET Smart Cities and as Youth Editor of the Journal of Information and Intelligence.

His main research areas include native intelligence at wireless communication, end-to-end transmission technology, computer vision, and integrated sensing and communication transmission.

 

Dr. Chenyuan Feng

EURECOM, France

Speech Title: Trustworthy Image Semantic Communication with GenAI: Explainablity, Controllability, and Efficiency

Abstract: Image semantic communication (ISC) has garnered significant attention for its potential to achieve high efficiency in visual content transmission. However, existing ISC systems based on joint source-channel coding face challenges in interpretability, operability, and compatibility. To address these limitations, we propose a novel trustworthy ISC framework. This approach leverages text extraction and segmentation mapping techniques to convert images into explainable semantics, while employing Generative Artificial Intelligence (GenAI) for multiple downstream inference tasks. We also introduce a multi-rate ISC transmission protocol that dynamically adapts to both the received explainable semantic content and specific task requirements at the receiver. Simulation results based on a real-world demo demonstrate that our framework achieves explainable learning, decoupled training, and compatible transmission in various application scenarios. Finally, some intriguing research directions and application scenarios are identified.

Biography: Dr. Chenyuan Feng, Ph.D, Marie Skłodowska-Curie scholar. Dr. Feng earned her Ph.D. from SUTD, Singapore, and is currently a research fellow at EURECOM, France. Her research interests include edge intelligence and AI for communication. Dr. Feng has published over 30 papers, including one ESI Top 1% Highly Cited Paper, one IEEE ComComAp 2021 Best Paper, and one IEEE ICCT 2024 Best Paper. Additionally, she has obtained five Chinese national invention patents and edited three books. She has also been recognized with First Prize in the International Postdoctoral Innovation and Entrepreneurship Competition, as well as one Gold and one Silver Award in the Chinese Internet+ Innovation and Entrepreneurship Competition. Dr. Feng has led several projects, including an EU Horizon's MSCA project (PI), a National Natural Science Foundation of China project (PI), a National Key R&D sub-project (co-PI), and an Enterprise Start-up Grant (co-PI and co-founder). She has served as a TPC member and delivered tutorials at several international conferences, such as IEEE ICCT, IEEE PIMRC, IEEE VCC, IEEE VTC-Spring, IEEE WiOpt, and IEEE Globecom. Furthermore, Dr. Feng serves as an Associate Editor for the IEEE Internet of Things Journal (IoTJ) and the IEEE Open Journal of the Communications Society (OJ-COMS).

 

Dr. Shuliang Gui

Chongqing University of Posts and Telecommunications, China

Speech Title: ISAC ISAR Imaging for Non-cooperation Moving Targets Sensing Based on Minimum Entropy Technology

Abstract: Integrated Sensing and Communication (ISAC) is poised to become a key technology for next-generation communication systems, with promising applications in areas such as low-altitude operations, security surveillance, and smart cities. Inverse Synthetic Aperture Radar (ISAR) technology plays a critical role in detecting and imaging moving targets. Motivated by ISAR imaging principles and leveraging the ISAC echo signal model, we propose a far-field wavenumber domain ISAR imaging method based on the minimum image entropy criterion, which enables multi-frame imaging of non-cooperative moving targets. Furthermore, Finally, to demonstrate the performance and feasibility of the proposed method, the real imaging experiments are conducted with an 5G millimeter-wave ISAC system.

Biography: Shuliang Gui (1993-), received the Ph.D. degree in signal and information processing from the University of Electronic Science and Technology of China, Chengdu, China, in 2020. He is currently working at the school of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China. His main research interests include integrated communication and sensing technology, millimeter-wave and terahertz radar fine imaging technology, and low-altitude UAV sensing technology. He has led more than 10 research projects, including the National Natural Science Foundation of China (NSFC) Youth Program, the Chongqing Natural Science Foundation General Program, the Chongqing Doctoral Express Project, the Chongqing Municipal Education Commission Science and Technology Innovation Project, and enterprise-commissioned projects. He has published over 20 papers in journals and conferences, including IEEE TGRS, IEEE TMTT, and Acta Electronica Sinica.