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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head>  <meta name="viewport" content="width=device-width; initial-scale=1.0; maximum-scale=1.0; user-scalable=0;"> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />  <title>EEIT 2024 | 工程教育与信息技术国际会议/Engineering Education and Information Technology</title> <link rel="shortcut icon" href="images/favicon.ico"/>  <link href="style.css" rel="stylesheet" type="text/css" /> <link href="style-responsive.css" rel="stylesheet" type="text/css" media="screen" /> <link href="css/font-awesome.css" rel="stylesheet" type="text/css" />  <link rel="stylesheet" href="css/libs/animate.css">  <link href="css/jquery.bxslider.css" rel="stylesheet" />  <link rel="stylesheet" href="layerslider/css/layerslider.css" type="text/css">  <script src="layerslider/js/jquery.js" type="text/javascript"></script> <script src="layerslider/js/greensock.js" type="text/javascript"></script>  <script src="layerslider/js/layerslider.transitions.js" type="text/javascript"></script> <script src="layerslider/js/layerslider.kreaturamedia.jquery.js" type="text/javascript"></script> <script src="js/bootstrap.min.js" type="text/javascript"></script>  <script src="js/jquery.bxslider.js"></script> <script> $(document).ready(function(){ $('.bxslider').bxSlider({ pager: false, controls: true, auto: true }); }); </script> <link rel="stylesheet" type="text/css" href="lightbox/jquery.fancybox.css" media="screen" /> <script src="lightbox/jquery.fancybox.js"></script> <script type="text/javascript"> $(document).ready(function() { $('.fancybox').fancybox(); }); </script>  <script type="text/javascript"> $(function() { $(window).scroll(function() { if($(this).scrollTop() != 0) { $('#gotop').fadeIn(); } else { $('#gotop').fadeOut(); } }); $('#gotop').click(function() { $('body,html').animate({scrollTop:0},800); }); }); </script> <script type="text/javascript"> if($(window).width() <= 900){ $(document).ready(function() { $('.mobile .title').click(function() { $(this).next("ul").slideToggle(); $(this).toggleClass("minus"); }); }); } </script> <style type="text/css"> .auto-style2 { text-align: justify; font-size: 100%; } .auto-style3 { font-size: 100%; } .auto-style4 { text-align: justify; } </style> </head> <body> <div class="header"> <div class="container"> <a href="#" class="logo"><img src="images/logo.jpg" width="1300" /></a> <div class="nav mobile"> <div class="title">Menu <span class="fa "></span></div> <ul> <li><a href="index.html">Home<br>主页</a></li> <li><a href="committee.html">Committee<br>组委会</a></li> <li class="active"><a href="keynote.html">Keynote Speaker<br>主旨报告</a></li> <li><a href="IS.html">Invited Speaker<br>特邀报告</a></li> <li><a href="cfp.html">CFP<br>征稿</a></li> <li><a href="sub.html">Submission<br>投稿须知</a></li> <li><a href="prog.html">Program<br>日程安排</a></li> <li><a href="attend.html">Join<br>注册 / 参会</a></li> <li><a href="history.html">History<br>历史</a></li> <li><a href="contact.html">Contact<br>联系方式</a></li> <li><a href="chi.html">CHN<br>中文</a></li> </ul> </div> </div> </div> <div class="wrapper"> <div class="feature_section" id="features"> <div class="container"> <div> <h2>Keynote Speaker </h2> <P> </P> <div class="testimonial_box"> <div class="quote_button"><img src="images/icons/i7.png" alt="" /></div> <div class="para"> <p><strong>Prof. O. Bonnaud</strong><br /> <strong>Emeritus Professor at University of Rennes, France<br /> Executive Director of National Coordination for Higher Education in Microelectronics and Nanotechnologies, GIP-P-CNFM, France<br /> Guest Professor at Southeast University, China<br /> </strong></p> </div> <div class="clientinfo"> <img height="131" src="images/expert/o.bonnaud.png" width="131" /></div> </div> <p align="justify" class="auto-style2"><strong>Speech Title: The Strategy of Microelectronics Education to Face the Future Challenges of The New Digital World</strong></p> <p align="justify" class="auto-style2"><strong>Abstract:</strong> The global development of digital technology has invaded our 21st-century world, and applies equally to industry, finance and government. This field has experienced exponential growth since 2005, accelerating with digital payments, and with the arrival of crypto-currencies, 5G-6G, and above all artificial intelligence (AI). Transparency on the user side of this digital world masks the fact that the associated consumption of energy and natural resources (rare elements) is also growing exponentially. In fact, we risk reaching a global energy impasse over the next decade, with digital energy consumption outstripping current global electricity production. The hardware part of the digital world is physically based on electronics and microelectronics. Today's challenge is to reduce the energy consumption of all electronics and minimize the use of rare elements in advanced technologies. The development of new technologies involving new component and circuit architectures and new materials should go some way towards meeting these needs. After presenting the context and challenges, various proposals for improving electronics, both technologically and architecturally, are detailed. But all these improvements can only be achieved if future employees in the sector are capable of innovation. Indeed, on a global scale, the microelectronics profession is experiencing a growing skills deficit, corresponding to a serious recruitment shortage. There is an urgent need to attract and train new specialists in this field. The final part of the presentation is devoted to the actions taken by the French national network for higher education in microelectronics to meet these challenges.</p> <p align="justify" class="auto-style2"><strong>Bio: </strong>Olivier Bonnaud, born in 1950 in France, is a student of the Ecole Normale Supérieure de Paris-Saclay and holds a PhD in microelectronics. In 1984, he became a full professor at the University of Rennes 1 and at Supelec (engineer school), where he created a microelectronics research laboratory that he directed until 2010, as well as several international masters and PhD programs in microelectronics engineering. He supervised 43 PhDs, worked in cooperation with microelectronics companies, on integrated and thin film technologies. He has published or presented more than 500 papers and written 7 books. He was member of more than 300 PhD defense juries, and chairman/co-chairman of more than thirty international conferences. <br /> Founder in 1985 of a regional inter-university joint center for microelectronics education (CCMO), he directed it until 2010, when he was appointed by the French Ministry of Higher Education as Executive Director of the National Coordination for Higher Education to Microelectronics and nanotechnologies (GIP-CNFM), a network of 12 French inter-university training centers that hosts about 20,000 students per year for practical training on technological platforms, including 7 cleanrooms. President of several scientific associations in electrical engineering, evaluator and expert for several research and higher education international agencies, he is professor emeritus since 2013. <br /> As part of his many international cooperation’s, he was selected for the "1000 global talents" program by the Chinese government in 2013. In 2018, he was awarded of the Jiangsu Province Friendship Medal for his 14 years scientific cooperation with SEU (Nanjing). Since 2019, he has been heavily involved in the French Strategic Committee of the Electronic Industry sector and is presently piloting a 5 years national project on “Skills and Jobs of the Future” in the field, in the frame of France 2030 governmental program.</p> <div> <P> </P> <div class="testimonial_box"> <div class="quote_button"><img src="images/icons/i7.png" alt="" /></div> <div class="para"> <p><strong>Prof. Kin K. Leung</strong><br /> <strong>Tananka Chair Professor of Imperial College, U.K.<br /> Fellow of the Royal Academy of Engineering<br /> Member of Academia European, IEEE Fellow, IET Fellow<br /> Imperial College, U.K.</strong></p> </div> <div class="clientinfo"><strong><img src="images/expert/KinKLeung.png" alt="" width="130" height="129" /></strong></div> </div> <p align="justify" class="auto-style2"><strong>Speech Title: Optimization by Learning and Federated Learning for Communication Networks</strong><br /> <br /> <strong>Abstract:</strong> Allocation of network resources to competing demands is an important problem for efficient design and management of future communication networks. The complexity of the issue is compounded by system dynamics in terms of fluctuation of resource demands and availability. On the future communication networks, users do not expect them to support only conventional multi-media services, but also future artificial intelligence (AI) and machine-learning (ML) applications for sensing and communications.<br /> <br /> In the first part of this speech, the speaker will discuss the issue of network resource allocation. Specifically, he will present a new machine-learning method by using two Coupled Long Short-Term Memory (CLSTM) networks to quickly and robustly produce the optimal or near-optimal resource allocation, which is modeled as constrained optimization problem, over a range of system parameters. Numerical examples for allocation of network resources will be presented to confirm the validity of the proposed method.<br /> <br /> In the second part, the speaker will present new approaches to supporting federated learning (FL) and improving the learning process by model pruning in communication networks with resource constraints. The FL technique learns the model parameters from data collected at distributed nodes and adapts according to the limited availability of resources. The key idea of model pruning is to remove unimportant model parameters to reduce computation and communication burden and speed up the learning convergence, while maintaining the model accuracy. Using real datasets, the experimentation results show that the proposed approaches perform near to the optimum or offer significant performance improvement over other methods.<br /> <br /> <strong>Bio:</strong> Kin K. Leung received his B.S. degree from the Chinese University of Hong Kong, and his M.S. and Ph.D. degrees from University of California, Los Angeles. He worked at AT&T Bell Labs and its successor companies in New Jersey from 1986 to 2004. Since then, he has been the Tanaka Chair Professor in the Electrical and Electronic Engineering (EEE), and Computing Departments at Imperial College in London. He also served as the Head of Communications and Signal Processing Group in the EEE Department at Imperial from 2009 to 2024. His current research focuses on optimization and machine learning for system design and control of large-scale communications, computer and quantum networks. He also works on multi-antenna and cross-layer designs for wireless networks.<br /> <br /> He is a Fellow of the Royal Academy of Engineering, IEEE Fellow, IET Fellow, and member of Academia Europaea. He received the Distinguished Member of Technical Staff Award from AT&T Bell Labs (1994) and the Royal Society Wolfson Research Merits Award (2004-09). Jointly with his collaborators, he received the IEEE Communications Society (ComSoc) Leonard G. Abraham Prize (2021), the IEEE ComSoc Best Survey Paper Award (2022), the U.S.–UK Science and Technology Stocktake Award (2021), the Lanchester Prize Honorable Mention Award (1997), and several best conference paper awards. He was an IEEE ComSoc Distinguished Lecturer (2022-23). He was a member (2009-11) and the chairman (2012-15) of the IEEE Fellow Evaluation Committee for the ComSoc. He has served as an editor for 10 IEEE and ACM journals and chaired the Steering Committee for the IEEE Transactions on Mobile Computing. Currently, he is an editor for the ACM Computing Survey and International Journal of Sensor Networks.</p> <P> </P> <div class="testimonial_box"> <div class="quote_button"><img src="images/icons/i7.png" alt="" /></div> <div class="para"> <p class="auto-style3"><strong>Prof. Jiangzhou Wang<br /> International Member of the Chinese Academy of Engineering (CAE)<br /> Fellow of the Royal Academy of Engineering (RAEng), U.K.<br /> Fellow of IEEE, Fellow of IET<br /> University of Kent, UK</strong></p> </div> <div class="clientinfo"> <img alt="" height="127" src="images/expert/wjz.png" width="131" /></div> </div> <p align="justify" class="auto-style2"><strong>Speech Title: mmWave Integrated Communications and Sensing </strong><br /> <br /> <strong>Abstract:</strong> Integrated communications and sensing (ISAC) has become very popular for the next generation mobile communications. This seminar will introduce the concept and challenges of using milimeter wave (mmWave) for ISAC. The latest research results in mmWave ISAC will be presented in conjunction with hybrid beamforming and rate splitting multiple access technologies. <br /> <br /> <strong>Bio:</strong> Jiangzhou Wang is a Professor with 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 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. He is/was the editor of multiple international journals, including IEEE Transactions on Communications from 1998 to 2013. 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.</p> <P> </P> <div class="testimonial_box"> <div class="quote_button"><img src="images/icons/i7.png" alt="" /></div> <div class="para"> <p class="auto-style3"><strong>Prof. Xiang-Gen Xia<br /> IEEE Fellow<br /> Chang Jiang Chair Professorship (visiting), China<br /> Charles Black Evans Professor<br /> University of Delaware, USA</strong></p> </div> <div class="clientinfo"> <img alt="" height="127" src="images/expert/xxg.png" width="131" /></div> </div> <p align="justify" class="auto-style4"><strong>Speech Title: Some Thoughts on 6G Modulation<br /> <br /> Abstract: </strong>I will talk about some of my own thoughts on 6G modulation. I think that 6G modulation should be a trade-off between complexity and performance. Two extremes are OFDM and single carrier frequency domain equalizer (SC-FDE). I will briefly introduce vector OFDM (VOFDM) that is in the middle of the two, and is a natural trade-off of complexity and performance, in particular for time-varying channels (delay Doppler channels).<strong><br /> <br /> Bio: </strong>Xiang-Gen Xia is the Charles Black Evans Professor, Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware, USA. Dr. Xia was the Kumar’s Chair Professor Group Professor (guest) in Wireless Communications, Tsinghua University, during 2009-2011, the Chang Jiang Chair Professor (visiting), Xidian University, during 2010-2012, and the World Class University (WCU) Chair Professor (visiting), Chonbuk National University, South Korea, during 2009-2013. He received the National Science Foundation (NSF) Faculty Early Career Development (CAREER) Program Award in 1997, the Office of Naval Research (ONR) Young Investigator Award in 1998, the Outstanding Overseas Young Investigator Award from the National Nature Science Foundation of China in 2001, and the Information Theory Outstanding Overseas Chinese Scientist Award from the Chinese Information Theory Society of Chinese Institute of Electronics in 2019. Dr. Xia was the General Co-Chair of ICASSP 2005 in Philadelphia. He is a Fellow of IEEE. His current research interests include space-time coding, MIMO and OFDM systems, digital signal processing, and SAR and ISAR imaging. He is the author of the book Modulated Coding for Intersymbol Interference Channels (New York, Marcel Dekker, 2000) and a co-author of the book Array Beamforming Enabled Wireless Communications (New York, CRC Press, 2023).</p> <P> </P> <div class="testimonial_box"> <div class="quote_button"><img src="images/icons/i7.png" alt="" /></div> <div class="para"> <p class="auto-style3"><strong>Prof. Guan Gui<br /> IEEE Fellow, IET Fellow<br /> AAIA Fellow, IEEE VTS Distinguished Lecturer<br /> Nanjing University of Posts and Telecommunications, China</strong></p> </div> <div class="clientinfo"> <img alt="" height="127" src="images/expert/gg.png" width="131" /></div> </div> <p align="justify" class="auto-style2"><strong>Speech Title: Intelligent Signal Sensing and Recognition Techniques Towards 6G</strong><br /> <br /> <strong>Abstract: </strong>The dawn of 6G wireless communication introduces a transformative era characterized by pervasive sensing and advanced intelligent identification, essential for ensuring physical security. This keynote speech highlights the integration of Artificial Intelligence (AI) and Deep Learning (DL) as pivotal in addressing the dynamic and complex challenges of 6G networks. We emphasize the role of AI in revolutionizing signal sensing and recognition. Our discussion centers on the application of these neural networks in enhancing signal detection, classification, and Specific Emitter Identification (SEI). By leveraging gradient-based optimization techniques, we demonstrate how ANNs can improve model and algorithm parameterization, leading to a data-driven approach that surpasses traditional rule-based systems. This advancement is crucial in the physical layer of wireless communications, where intelligent signal recognition plays a key role in maintaining security and efficiency. We also explore the challenges faced by conventional model-based methods in the evolving landscape of 6G communication systems, which are marked by complex interference and uncertain channel conditions. DL emerges as a solution, offering innovative strategies for redesigning baseband module functionalities, including coding/decoding and detection processes. In conclusion, this keynote underscores the significance of integrating intelligent signal sensing and recognition with DL technologies in 6G networks. This approach not only enhances physical security but also paves the way for a more robust, efficient, and intelligent wireless communication ecosystem, capable of meeting the security demands of the future.<br /> <br /> <strong>Bio: </strong>Guan Gui received the Ph.D. degree from the University of Electronic Science and Technology of China, Chengdu, China, in 2012. From 2009 to 2014, he joined Tohoku University as a Research Assistant and a Post-Doctoral Research Fellow. From 2014 to 2015, he was an Assistant Professor with Akita Prefectural University, Akita, Japan. Since 2015, he has been a Professor with the Nanjing University of Posts and Telecommunications, Nanjing, China. He has published more than 200 IEEE journals/conference papers. His recent research interests include intelligence sensing and recognition, intelligent signal processing, and physical layer security. Dr. Gui contributions to intelligent signal analysis and wireless resource optimization have earned him the title of fellow of the IEEE, IET, and AAIA. He was a recipient of several Best Paper Awards, such as ICC 2017, ICC 2014, and VTC 2014-Spring. He received the IEEE Communications Society Heinrich Hertz Award in 2021, top 2% scientists of the world by Stanford University from 2021 to 2023, the Clarivate Analytics Highly Cited Researcher in Cross-Field from 2021 to 2023, the Highly Cited Chinese Researchers by Elsevier from 2020 to 2023, a member and Global Activities Contributions Award in 2018, the Top Editor Award of IEEE Transactions on Vehicular Technology in 2019, the Outstanding Journal Service Award of KSII Transactions on Internet and Information System in 2020, the Exemplary Reviewer Award of IEEE Communications Letters in 2017, the 2012 Japan Society for Promotion of Science (JSPS) Postdoctoral Fellowships for Foreign Researchers, and the 2018 Japan Society for Promotion of Science (JSPS) International Fellowships for Overseas Researchers. He was also selected as the Jiangsu Specially-Appointed Professor in 2016, the Jiangsu High-Level Innovation and Entrepreneurial Talent in 2016, and the Jiangsu Six Top Talent in 2018.</p> </div> </div> </div> </div> <div class="common_section"> <div class="container"> <div class="copyright">Copyright © 2024. 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