Biography: Professor Lei Chen is a chair professor in the data science and analytic thrust at HKUST (GZ), Fellow of the IEEE, and a Distinguished Member of the ACM. Currently, Prof. Chen serves as the dean of information hub, the director of Big Data Institute at HKUST (GZ). Prof. Chen’s research interests include Data-driven AI, Big Data Analytics, Metaverse, knowledge graphs, blockchains, data privacy, crowdsourcing, spatial and temporal databases and probabilistic databases. He received his BS degree in computer science and engineering from Tianjin University, Tianjin, China, MA degree from Asian Institute of Technology, Bangkok, Thailand, and PhD in computer science from the University of Waterloo, Canada. Prof. Chen received the SIGMOD Test-of-Time Award in 2015, Best research paper award in VLDB 2022.The system developed by Prof. Chen’s team won the excellent demonstration award in VLDB 2014. Prof. Chen had served as VLDB 2019 PC Co-chair. Currently, Prof. Chen serves as Editor-in-chief of IEEE Transaction on Data and Knowledge Engineering and General Co-Chair of VLDB 2024.

Title: Data Science for Large Models

Abstract: Large Models (LM) has made significant progress and found wide application in various fields, like LLM for question answering. However, the success and efficiency of LM models depend on proper data management. Training a LM is challenging without labeled data, and efficiency is hindered by large datasets, complex models, and numerous hyperparameters. Lack of validation and explanation limits model applicability. In this talk, I will discuss three crucial issues in data science for large models: 1) effective data preparation for LM, including data selection; 2) LM training optimization, involving computation graph optimization; and 3) the importance of model explanation for robustness and transparency. I will conclude by highlighting future research directions on data science for large Models.

Biography: Mr. Hui Wang , President of Huawei NCE Data Communication Domain, is in charge of the strategic planning, competitiveness building, and industrial pattern building of Huawei Qiankun CloudService and autonomous driving network (ADN) products. Prior to the current position, Mr. Wang took charge of iMaster NCE Data Center Product，iMaster NCE Campus Product，Digital Services and other products, and successfully built the industry's first L3.5 enterprise autonomous driving network (ADN) solution. He is committed to building the industry-leading network digital map and network large model products to accelerate industry digitalization.

Title: Large Model Enables IP Networks to Move Towards High-Level Self-Intelligence

Abstract: As one of the key technologies of the 4th industrial revolution, large model is leading this wave of transformation with its unique advantages. Huawei Cloud Pangu Weather AI Model can predict the weather of the next seven days within just 10 seconds, 10,000 times faster than the traditional weather forecast. JPMorgan Chase already begins to apply an AI large language model (LLM) to speculate on emotional changes and evaluate monetary policies from the public speeches by 17 Fed officials. However, network management in the large model era still faces many challenges such as real-time decision-making, rigorous inference, and scenario generalization. Against this backdrop, Huawei proposes a three-layer intelligent network architecture (intelligent NE, digital twin, and smart brain), aiming to accelerate the implementation of L4 high-level intelligence of IP networks and boost new quality productive forces.

Biography: Prof. George C. Polyzos is with the School of Data Science, The Chinese University of Hong Kong, Shenzhen, on leave from the Athens University of Economics and Business. Previously, he was Professor of Computer Science and Engineering at the University of California, San Diego, where he was co-director of the Computer Systems Laboratory, member of the Steering Committee of the UCSD Center for Wireless Communications and Senior Fellow of the San Diego Supercomputer Center. His current research interests include security and privacy, Internet architecture and protocols, the Internet-of-Things, the Smart Energy Grid, mobile multimedia communications, wireless networks, and performance analysis of computer and communications systems. Dr. Polyzos has led many research projects at UCSD and AUEB. Under his leadership his lab has participated in a series of Research projects funded by the European Commission (PSIRP, PURSUIT and POINT) that developed Publish-Subscribe Internetworking, an Information-Centric Networking (ICN) architecture. PURSUIT received the Future Internet Award in 2013. Prof. Polyzos received his Diploma in Electrical Engineering from the National Technical University in Athens, Greece and his M.A.Sc. in Electrical Engineering and Ph.D. in Computer Science from the University of Toronto. He has served on journal editorial boards and on the program committees of many conferences and workshops and he has chaired the Steering Committee of the ACM SIGCOMM conference on Information-Centric Networking. He has been reviewer and panelist for the US National Science Foundation, the European Commission and other research funding agencies.

Title: Automating and Enhancing the Security of the Software Supply Chain

Abstract: The software ecosystem has become very complex and its supply chains involve many entities, components, and processes, of varying complexity, roles, value, and security. The software supply chain becomes often the target of high-profile attackers and persistent attacks with widespread impact. Modern supply chain tracing techniques and transparency services promise to improve the security and trustworthiness of software. However, this task entails many, currently open, challenges. Firstly, the attack surface of the software supply chain is vast. Secondly, software development involves a multitude of tools and external components. Thirdly, software development and maintenance governance is complex. Finally, supply chain attack detection and mitigation require access to diverse types of techniques and information. We investigate and develop processes and tools that provide responses to questions about software transparency services: what information is recorded, who can record information, and how risks can be mitigated by extracted information. Outcomes allow software companies, developer communities, and end-users to make informed and mostly automated decisions related to the security of the software supply chain. We promote decentralization by empowering users to depart from the legacy Web PKI system traditionally used for "signing" information related to software, as well as by enabling decentralized governance of transparency registries. In addition, we investigate artificial intelligence techniques to discover malware components and threats in software to augment transparency services.

Biography: David Lu served in various leadership positions at AT&T that resulted in multibillion-dollar savings over the past 35 years. Currently holds 60+ patents and frequently appears as speaker at technical and leadership seminars and conferences throughout the world. Led global R&D organizations of more than 5,000 people at AT&T. Was responsible for the next generation SDN automation platform enabling AT&T’s network virtualization and 5G/Fiber networks. Well respected as an inspirational industry leader in hyper scale software and AI driven platforms with institutional knowledge and world leading expertise achieving best in class quality, reliability, speed, and demonstrable financial/service benefits! Work pioneered many of the world’s first innovations and promoted many distinguished industry leaders and technical talents. Awards received include CIE-USA AAEOY Engineer of the Year Award in 2017 and Executive of the Year Award in 2023, IEEE CQR Chairman’s Award, CIO 100 Award, AT&T Innovation and Patent Awards, and AT&T Corporate Leadership Award. Actively engaged in community, professional, and faith work.

Title: Inspire Forward Technology & Into Humanity

Abstract: The rapid technology innovation has changed our life so dramatically in the last two decades we never seen in human history. The digital transformation fueled by the software driven everything, cloud computing, robotics, semiconductor, big data analytics, new generation of ultrafast mobile communication (terrestrial and low earth orbit satellites), quantum computing, super-scale data models and generative AI, and regenerative medicine will change the world we know today in an unprecedented pace! As those of us, who are in the center of science and engineering making these happen, we must also take a harder look at the impact the technology change brings us, to prevent the negative impact but propel the positive changes focusing on usability and adaptability, i.e., user centered sustainable growth and sound environmental practices.
The talk will highlight the industry revolution and innovation that took place, are taking place in front of our eyes, and what could come in next decades. It will focus on the human impact of these changes and ways we could cope, adapt, and lead the positive changes to the social structure and communities to a brighter future!

Biography: Prof. Yuan Wu is currently the Associate Professor with the State Key Laboratory of Internet of Things for Smart City, University of Macau, Macao, China, and also with the Department of Computer and Information Science, University of Macau. His research interests focus on edge computing and edge intelligence. He received the Best Paper Award from IEEE ICC’2016, IEEE TCGCC’2017, and WCNC’2023. He served as the symposium TPC co-chairs for GLOBECOM’2024, ICCC’2023, VTC’2022-Spring, etc. He is currently on the editorial board of IEEE TWC, TVT, and TNSE. He is a senior member of IEEE and distinguished member of CCF, and he currently serves as the Vice Chair of IEEE ComSoC Macau Chapter.

Title: The Convergence of Generative AI and Federated Learning for Efficient and Personalized Edge Intelligence

Abstract: Recent advancements in generative artificial intelligence (AI) and federated learning (FL) have opened new avenues for efficient and personalized edge intelligence. This talk will explore the synergies between generative AI and FL within the realm of edge computing. Generative AI, particularly through large language and vision models, has demonstrated remarkable capabilities in synthesizing realistic data. In parallel, federated learning facilitates collaborative model training across distributed edge devices while ensuring data privacy. This talk will introduce a novel framework for on-demand generative AI services tailored for edge computing. This discussion will focus on how generative AI can be delivered to heterogeneous edge devices, accommodating varying latency and quality requirements. Additionally, the talk will highlight the potential benefits of integrating generative AI with FL to enhance resource efficiency in edge intelligence. By leveraging generative models to create synthetic training data, we can augment limited local datasets on edge devices. This balance between local and synthetic data allows FL systems to achieve fast and accurate convergence. Finally, the talk will address future research directions and challenges, paving the way for further advancements in this exciting field.

Biography: Prof. Huaiguang Jiang is a tenured Professor of the School of Future Technology, South China University of Technology. He is now a standing committee member of Guangzhou Youth Federation and deputy director of Science and Technology Field, his research attention focuses on low-carbon intelligent energy and unmanned automation . He was selected as a National-level young talent, and has undertaken and participated in scientific research projects at national and other levels for many times, with a total project fund of more than 10 million RMB. As a senior member of IEEE, he has published more than 50 Chinese and English papers and works in related fields, with a total impact factor of more than 100, invited to publish 2 English academic monographs, participated in, chaired and organized the top Chinese and English conferences for many times, and was invited to review more than 20 top journals and top conferences in the industry.

Title: TBA

Abstract: TBA

Biography: Jiangzhou Wang (IEEE Fellow) is a Professor at the University of Kent, U.K. His research interest is in mobile communications. He has published over 400 papers and 4 books. He was a recipient of the 2022 IEEE Communications Society Leonard G. Abraham Prize and the 2012 IEEE Globecom Best Paper Award. Professor Wang is a Fellow of the Royal Academy of Engineering, U.K., Fellow of the IEEE, and Fellow of the IET. He was the Technical Program Chair of the 2019 IEEE International Conference on Communications (ICC2019), Shanghai, the Executive Chair of the IEEE ICC2015, London, and the Technical Program Chair of the IEEE WCNC2013.

Title: Intelligent Reflecting Surfaces (IRS) for 6G Mobile Communications

Abstract: While the design of the Intelligent Reflective Surface (IRS) has a long history in the electromagnetic literature, communication applications are still in their infancy. Recently, IRS-assisted wireless communication has received considerable attention because of its ability to support cost-effective and energy-efficient high data rate communications for next-generation mobile communications. This talk will explain why 6G mobile communications require an IRS, and what its application and technical challenges are. It also introduces the latest research results of the IRS.

Biography: Rose Qingyang Hu is Professor with the Electrical and Computer Engineering Department and Associate Dean for research of College of Engineering at Utah State University. She also directs Communications Network Innovation Lab at Utah State University. Besides decades of academia research experience, she has more than 10 years industrial R&D experience with Nortel, Blackberry, and Intel as a technical manager, a senior research scientist, and a senior wireless system architect, actively participating in industrial 3G/4G technology development, standardization, system level simulation and performance evaluation. Her current research interests include next-generation wireless system design and optimization, Internet of Things, Cyber Physical system, Mobile Edge Computing, artificial intelligence in wireless networks. She has published over 300 in leading IEEE journals and conferences and also holds 30+ patents in her research areas. Rose Hu is an IEEE Fellow, IEEE Communications Society Distinguished Lecturer 2015-2018, IEEE Vehicular Technology Society Distinguished Lecturer 2020-2022, NIST Communication Technology Laboratory Innovator 2020, and a recipient of Best Paper Awards from the IEEE GLOBECOM 2012, the IEEE ICC 2015, the IEEE VTC Spring 2016, and the IEEE ICC 2016. She is currently serving as the IEEE ComSoc BoG Chief Information Officer, Associate Editor-In-Chief of IEEE Commutations Magazine, and ASEE Engineering Research Council Board of Director. She is also serving on the editorial boards of the IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, and IEEE Wireless Communications.

Title: Federated Learning with Efficiency and Privacy Considerations in Wireless Networks

Abstract: Centralized data collection and training in conventional machine learning (ML) algorithms have raised many concerns including privacy restrictions and communication cost due to massive amount of data transfer. Federated leaning (FL) exploits the rapidly growing computational capacity in small local devices and allows these devices to train ML models locally and only exchange the trained model parameters with the edge server. Through this, FL can greatly alleviate data privacy concern, reduce communication cost, and help build a scalable centralized ML model. FL methods offer a number of prominent advantages, including scalability and data privacy. On the other hand, a large-scale wireless network normally involves many heterogeneous devices with varying constraints and encounters very dynamic channel environments. This raises many challenges such as system heterogeneity, statistical heterogeneity, privacy and security, user scheduling, fairness in FL. This talk will present some of our recent research outcomes on model parameter transmission schemes and user scheduling strategies in FL that tackle these challenges. Techniques such as NOMA and over-the-air computation are introduced to achieve fast ML training. Model parameter compression and sparsification are further introduced to reduce the wireless communication cost. Moreover, model update-based aggregation is applied to defend against Byzantine attacks and individual client model initialization schemes are exploited to enhance privacy protection in FL.

Biography: Since joining AT&T Bell Labs in 1987, David has served in various leadership positions at AT&T. He has led numerous automation initiatives in AT&T that resulted in multibillion-dollar savings over the past 20 years. David holds 57 patents and frequently appears as a guest speaker at technical and leadership seminars and conferences throughout the world. He has received numerous industry awards including the 2015 Chairman’s Award from IEEE Communication Society Communications Quality and Reliability Technical Committee and 2017 CIE AAEOY (Asian America Engineer of Year) Award. David Lu currently leads a global team of more than 2,500 people responsible for the architecture, development, and engineering of AT&T’s next generation SDN (Software Defined Network) automation platform and open source (Linux Foundation ONAP) enabling AT&T’s network virtualization and target network systems transformation including PaaS & SaaS, policy control & orchestration, hyper-automation and AI/ML driven data analytics. David is a well-respected leader in large scale, real time software architecture and development, network performance and traffic management, workflow and policy-controlled automation, large databases and big data implementation/mining/analytics, machine learning, artificial intelligence, software reliability and quality, and network operations process engineering.

Title: Collision of Next Generation Communication Technologies

Abstract: The world of communication technology has rapidly evolved from coaxial to fiber, from wireline to wireless, from low speed to super highspeed broadband, from 4G wireless to 5G and other breakthrough technologies such as LEO (Low Earth Orbit) satellite communication networks, from hardware centric architecture to software centric architecture. These changes not only brought transformational impact to the science and technology fields but also enabled use cases that would introduce unimaginable economical and social impact to the world in the next 2 decades.
This talk will provide an industry landscape while focus on the latest technology development in the communication field as well as specific use cases that might be enabled by 5G, 5G+, 6G terrestrial wireless networks, LEO satellite communication networks, multi-gig consumer and business broadband services, ultrafast and multi Tera-bits optical networks, and virtualized software centric networks. The talk will highlight the industry operational challenges in implementing such transformation, especially the AI driven network & operations, and business use cases for these technology advancements. In particular, the talk will cover a) 5G Slicing & On-demanding network capacity, b) Neural Networking using Deep Learning analytics, c) Millimeter wave length technology and operation challenges and use cases, d) Smart City 5G current and future use cases, e) Future of ORAN and meeting its requirements with ONAP (Open Network Automation Platform).

Biography: Dr. Chih-Lin I received her Ph.D. degree in electrical engineering from Stanford University. She has been working at multiple world-class companies and research institutes leading the R&D, including AT&T Bell Labs; Director of AT&T HQ, Director of ITRI Taiwan, and VPGD of ASTRI Hong Kong. She received the IEEE Trans.COM Stephen Rice Best Paper Award, is a winner of the CCCP National 1000 Talent Program, and has won the 2015 Industrial Innovation Award of IEEE Communication Society for Leadership and Innovation in Next-Generation Cellular Wireless Networks. In 2011, she joined China Mobile as its Chief Scientist of wireless technologies, established the Green Communications Research Center, and launched the 5G Key Technologies R&D. She is spearheading major initiatives including 5G, C-RAN, high energy efficiency system architectures, technologies and devices; and green energy. She was an Area Editor of IEEE/ACM Trans.NET, an elected Board Member of IEEE ComSoc, Chair of the ComSoc Meetings and Conferences Board, and Founding Chair of the IEEE WCNC Steering Committee. She was a Professor at NCTU, an Adjunct Professor at NTU, and currently an Adjunct Professor at BUPT. She is the Chair of FuTURE 5G SIG, an Executive Board Member of GreenTouch, a Network Operator Council Founding Member of ETSI NFV, a Steering Board Member of WWRF, a member of IEEE ComSoc SDB, SPC, and CSCN-SC, and a Scientific Advisory Board Member of Singapore NRF. Her current research interests center around "Green, Soft, and Open".

Title: TBD

Abstract: TBD

Biography: Anup Kumar Anup Kumar is currently a Professor of Computer Science and Engineering Department at the University of Louisville. He is also the Director of Mobile Information Network and Distributed Systems (MINDS) Lab. His research interests include distributed system modeling, network security, and mobile computing. He is an Associate Editor of Internal Journal of Web Services Research. He was an Associate Editor of IEEE Transactions on Services Computing and International Society of Computers and Their Application Journal. He was a member of IEEE Distinguished Visitor Program (2006-2008). He was the Chair of IEEE Computer Society Technical committee on Simulation (TCSIM) (2004-2007). He has published and presented over 200 papers. Some of his papers have appeared in ACM Multimedia Systems Journal, several IEEE Transactions, Computer, IEEE Transactions of Reliability, Journal of Parallel and Distributed Computing, IEEE Journal on Selected Areas in Communications etc. He was the Associate Editor of IEEE Transactions on Services Computing for four years and International Journal of Engineering Design and Automation from 1995-1998. He has served on many conference program and organizing committees such as CyberC-2020, IEEE ISCC 2007, IEEE ICSW-2006, IEEE MASS-2005, IEEE SCC-2005, IEEE ICWS-2005, CIT-2005, IEEE MASCOTS, ADCOM 97 and 98. He has also edited special issues in IEEE Internet Magazine, and International Journal on Computers and Operations Research.

Title: Reset Based Recovery Mechanism through Entropy Cutoff to Counter BUS-OFF Attacks

Abstract: The CAN BUS operations provides significant communication infrastructure for interaction between various components in a vehicle. An alarming number of attacks exploit the built-in CAN bus error handling mechanism by launching various attacks either through wired/wireless medium. Security of message communication is given the least priority over the protocol operation. This talk plans to explore the error handling mechanism built-in the control area network (CAN) node through our strategic experimentations by generating errors and forcing the compromised CAN nodes to three error states i.e. Error-Active, Error- Passive and BUS-OFF state. These BUS-OFF attacks exploit weaknesses in security measures to make CAN bus operation malfunction. Since, CAN ECUs are not expected to leave error-active state except under some exceptional conditions, BUS-OFF attacks are understudied and under explored. The solution discussed in this talk is based on MAC based encryption-decryption through block chain methodology to provide robust functionality. The proposed method is significant in terms of not impacting other nodes in the CAN bus and also having the ability to mitigate BUS-OFF attack by detecting it without impacting preceding or succeeding CAN message frames.

Biography: Rentao Gu, Vice Dean and Professor in School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), China. He received the Ph.D. degree from BUPT in 2010. From 2008-2009, he studied in Networks and Learning Lab in Georgia Institute of Technology, USA, as a visiting scholar. Since 2010, he has joined BUPT as a faculty member. After that, as the project leader and principal researcher, he has successively undertaken more than 10 national, ministry-level research projects related to the software defined optical networks, 5G transport network, and AI enabled networking. He has held more than 30 U.S. invention patents and Chinese invention patents, and published many peer-reviewed journals and conferences papers. His inventions and technical contributions were awarded the National Science and Technology Progress Award of China and several other science and technical awards.
Rentao served in the Organizing Committee/Technical Program Committee of various international conferences (such as GLOBECOM/ICC/NFV-SDN), was Young Professional Standing Committee Member of IEEE Communication Society from 2016 to 2017 and MDC member of IEEE Computer Society from 2012 to 2013. He is currently the Lead Coordinator of Region 10 Young Professional Committee. Rentao is a Senior Member of the IEEE.

Title: AI Enabled Autonomous Optical Networks

Abstract: The emerging services require network with high bandwidth, large-scale connection, low-latency and high reliability, which urgently require the network itself to carry out “intelligence upgradation”. In particular, the operation optimization of optical networks becomes more complex and difficult, due to state unawareness, higher resource dimensions in the optical layer, and much more constraints in the optical network. Artificial intelligence and open programmability have improved the perception, decision-making and execution capabilities of optical networks, and promoted optical networks to move towards "intelligent autonomy". However, the complexity of optical networks and the limitations of current artificial intelligence algorithms still face many challenges. This talk will review the history of optical network intelligence development, analyze the essential logic and key technologies of the development trend, and introduce the progress in optical network perception, transmission, decision-making, etc.

Biography: Guangxia Xu, Professor and Ph.D. Adviser in Cyberspace Institute of Advanced Technology, Guangzhou University. She is currently a Senior Member of the China Computer Federation (CCF), Blockchain Committee member of CCF, ACM and Senior IEEE member. She has served as the Director of Big Data Security and Intelligence Analytics Technology Innovation Team at Chongqing University. She was a Visiting Scholar at the Stevens Institute of Technology, New Jersey, USA.
Her research interests include Cyberspace Security, IoT Security, Big Data Security and Analytics, Blockchain Technology and AI Security. Extensive and novel results have been accomplished and most of them have already been published through high-quality journals, conference papers and projects. She was in charge of National Science and Technology Support Projects, National Natural Science Foundation of China, Information Security Projects of National Development and Reform Commission, and many more. In addition, she is a reviewer or editorial board member for ACM Computing Surveys, Digital Communications and Networks, and so on.

Title: TBD

Abstract: TBD

Biography: Dr. Jiaming ZHANG is currently a Research Fellow and Head of the Rehabilitation Robotics Lab in the Institute of Robotics and Intelligent Manufacturing, the Chinese University of Hong Kong (Shenzhen), Shenzhen, China. He joined the Neurocomputing and Robotics Group led by Prof. Noel Sharkey and Dr. Amanda J.C. Sharkey, in the Department of Computer Science, University of Sheffield in October, 2008, and completed his Ph.D. in Computer Science in Spring, 2013. He received B.Sc. in Communication Engineering and M.Sc. in Control Systems in Chongqing University, China and in the University of Sheffield, UK, respectively. Before he moved to Shenzhen, he joined the Advanced Robotics Lab (ARL) in the Chinese University of Hong Kong, Hong Kong, as an assistant research fellow. Currently He has led over 3 and participated as a core member in 8 national, provincial and municipal research/industrialization projects (more than 10 million RMB funds granted), and has published more than 15 research articles and has applied for more than 20 patents in the field of robotics and AI. Dr. ZHANG is a member of Guangdong Association for Artificial Intelligence and Robotics, and a member of Guangdong Society of Image and Graphics. Dr. ZHANG also served as a visiting associate research fellow in Peng Cheng Laboratory (a National Key Laboratory based in Shenzhen)，and in Shenzhen Institute of Artificial Intelligence and Robotics for Society, in 2021. His research interests include Socially Interactive Robots, Health Care Robotics, Marine Robotics, Pattern Recognition and Artificial Intelligence, Deep Reinforcement Learning, Robotic Hardware and Smart Sensors Design.

Title: Enhancing Capabilities of Medical Robotic Platforms with Deep Learning and AI

Abstract: Big data and machine learning are having an impact on most aspects of healthcare. In recent years’ patient-centered care has greatly utilized the latest technologies of artificial intelligence (AI) and robotics to support diagnosis, decision-making and treatment. Example use cases of deep learning (DL) and AI deployed in two different medical robotic platforms, e.g., a socially interactive robot for autistic rehabilitation, and a 5G mobile platform for telemedicine such as dermatology, will be presented in this talk. DL frameworks and algorithms such as Intention Understanding, Attention-Based Interaction, and how they enhance some key capabilities of robotic platforms, will be elaborated. Potential use of AI and robotic applications in healthcare will be also discussed in this talk.

Biography: Dr. Xiaoqun Zhang is a distinguished professor at School of mathematics Sciences and Institute of natural sciences in Shanghai Jiao Tong University. She received her Bachelor and Master degrees from Wuhan University and obtained her PhD degree in Applied Mathematics from University of South Brittany, France. She worked in University of California, Los Angeles as a CAM Assistant Professor. Her research interests include mathematical modeling and algorithms for imaging, data science and machine learning.

Title: Medical Image Reconstruction from limit data: from sparsity to deep learning

Abstract: Along with the rapid development of modern medical imaging technologies and computational resource, medical images play more and more important roles in various clinical applications. However, there still present many modeling and computational challenges for reconstruct medical images with high accuracy and efficiency in practice, especially from limited and corrupted data due to data acquiring speed acceleration and radiation dose reduction. In this talk, I will first present sparsity promoting and redundancy exploring approaches for some classes of image restoration problems, such as multi-modality image and dynamic images. Then I will present deep learning-based approaches for image reconstruction in both supervised and unsupervised regimes, along with two typical medical image reconstruction tasks: fast MRI and low dose CT.

Biography: Dr. Weihua Ye currently serves as a Director Member of Technical Staff at AT&T Labs. She has over 20 years of experience in the wireless industry, with a Ph.D. from Syracuse University in Electrical Engineering and an MBA from the Kellogg School of Management, Northwestern University. Since 2005, Weihua has taken on various technical and leadership roles at AT&T, including engineering manager, Radio Access Network (RAN) platform architect, and wireless analytics & automation lead. She exhibits great passion with an outstanding track record of improving both network performance and customer experience.
Weihua challenges herself and others to think outside of the box, take a holistic approach, and embrace partnership. Her network analytics team has developed a popular mobility tool suite with over 80K usages per month, which is able to provide remote testing and scaled screening of passive intermodulation, check mobility customer quality, and diagnose root causes. It reduces the number of cell site visits (avoiding over $15M in annual costs) and improves mean time to resolution. Weihua is instrumental to driving RAN openness and automation, being one of AT&T's key contributors in establishing the industry's O-RAN alliance. In 2017, her team successfully prototyped an automated closed-loop algorithm and demonstrated the feasibility of near real time RAN control. In following years, three use cases have been developed and taken through field trials. For over two years, her team represented AT&T in O-RAN as the co-chair of WG2. By giving innovations a practical application, Weihua has helped shape the future of open and software-defined RAN. Her recent project on end-to-end cross-layer diagnostics and geolocation-based analytics is revolutionizing wireless service assurance and network optimization.
Dr. Ye has seven papers published in prestigious journals and conferences, as well as ten patents issued by the IJSPTO. She and her husband have two children, a rising college freshman and a high school sophomore. Outside of work, Weihua enjoys music, reading, and hiking. She also runs marathons.
Dr. Ye received the 2022 Asian American Engineers of the Year (AAEOY) Award from the Chinese Institute of Engineers, USA (CIE/USA). The Institute was established in 1917.

Title: Mobile Network Instrumentation in Support of Customers' Quality of Experience

Abstract: A 'Good Network' is not something that customers can pick up, experience directly, and evaluate on its own merit. Applications are the interface through which customers interact with mobility products. However, the relationship between application behavior and the underlying network is very complex – too few resources can cause the application to fail catastrophically, while too many resources can be wasteful with no customer benefit. Studying Application Experience Metrics and determine "What do applications actually need from the Mobility Network to create a 'good' customer experience?" is fundamental not only to improve customer experience, but also to unlock opportunities for premium services and product differentiation. To ensure network meets the application QoE requirements, we need comprehensive instrumentation for every segment of network across RAN, Transport, and Mobility Core, as well as an end-to-end performance model built upon them. Historically operators have favored the average or peak performance metrics. Recent customer surveys in the industry indicate that the customer experience is more relevant to bottom percentile in stats than top percentile, which embodies a focus on the consistency and reliability of the network.

Biography: Prof. Fei Ma is currently the Associate Vice President (research) of Xi'an Jiaotong-Liverpool University, and a Professor of Applied Mathematics department. He obtained his BSc. And MSc. both in computational mathematics in 1999 and 2002 respectively. In 2008, he obtained his Ph.D. in applied mathematics from the Flinders University of Australia.
Prof. Fei Ma worked as a software engineer in Shenzhen Kingdee Software Co., Ltd. during 2002 and 2004. After he completed his PhD, he worked as a mathematics lecturer as well as a research fellow in Flinders University. In 2009, he joined Symbion, Australia's second largest pharmaceutical wholesaler, as an analyst of national inventory center. In 2012, he joined Xi'an Jiaotong-Liverpool University, where he has served as the director of the Center for Mathematics and Physics, the acting and deputy head of the Department of Mathematics, and the policy dean of research and graduate studies of the university.
Prof. Fei Ma’s research interests include medical image analysis, particularly on computer aided breast cancer diagnosis with mammogram and chromosome image analysis; big data analytics; inventory forecasting; and graph matching. He has published more than 60 international journal and conference papers, and has been the PI, co-PI and member of more than 20 external research grants. He was the founder and the first director of the intelligent computing and fintech lab. He was a member of standing committee of China Higher Education Society Educational Mathematics Committee, a board member of Cambricon Fintech Research Institute, and a member of China Society for Industrial and Applied Mathematics (CSIAM) Financial Technology and Algorithm Professional Committee (Preparatory).

Title: Artificial intelligence and medical image processing

Abstract: TBD

Biography: Dr. Yi Wang [SM'11] is a research expert at Huawei Technologies Co., Ltd. in Shanghai. He received the M.S.E.E and Ph.D. degrees from information engineering department at Beijing University of Posts & Telecommunications, China, in 1997 and 2000 respectively. He was one of the initial researchers of FuTURE program in 863 when he worked in Tsinghua University during 2000-2002. He visited the University of Kiel in Germany as senior researcher during 2002-2004. Since 2005 he joined Huawei Technologies Co., Ltd. in Shanghai, he led a series of research projects on LTE/LTE-Advanced and 5G systems. Currently he is leading 5G positioning and sensing research in Huawei. Dr. Yi Wang has published over 300 patents and 80 papers. Many patents have been realized in LTE/LTE-Advanced and 5G products and adopted in 3GPP and IEEE802.11 standards.
Dr. Wang is the vice chair of IEEE Chapter in Shanghai. He was the board member of NYU Wireless Industrial Affiliates during 2014 – 2017, the chair of China IMT-2020 (5G) mmWave Technology during 2013 – 2017, the vice chair of WWRF WG4 during 2008-2010.

Title: 5G Positioning from an Industry Perspective

Abstract: Driven by the regulatory services (e.g. FCC E911) and the explosive growth of localization market, 3GPP has taken positioning into standardization from 2G to 5G. Standardization of the 5G positioning started in 2017, and has, so far, been within Release 15 (Rel-15), Rel-16, Rel-17, and part of Rel-18 in 2022. Meanwhile, many industries are deploying 5G positioning for commercial usages particularly for indoor and factory scenarios. In this talk, we will 5G positioning requirements and use cases, followed by 5G positioning standards and candidate algorithms. Finally, the latest field-trial results of 5G positioning, e.g., UL-TDOA positioning and carrier phase positioning, will be presented to show the how accuracy 5G positioning can achieve.

Biography: Prof. Ning Wang
received the B.E. degree in communication engineering from Tianjin University, China, in 2004, the M.A.Sc. degree in electrical engineering from The University of British Columbia, Canada, in 2010, and the Ph.D. degree in electrical engineering from the University of Victoria, 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 planning and optimization of commercial mobile communication networks. From 2013 to 2015, he was a Postdoctoral Research Fellow with the Department of Electrical and Computer Engineering, The University of British Columbia, Canada. Since 2015, he has been with the School of Information Engineering, Zhengzhou University, China, where he is currently a full Professor. In 2017, he was a Visiting Researcher in the Department of Electronic Engineering, Tsinghua University, China. He also holds adjunct appointments with the Department of Electrical and Computer Engineering, McMaster University, Canada, and the State Key Laboratory of Millimeter Waves, Southeast University, China.
Prof. Wang's research interests include resource allocation and security designs of wireless networks, channel modeling for wireless communications, statistical signal processing, and cooperative wireless communications, and he has published over 100 papers in these areas. He was the recipient of the Rising Star Award of ACM China Zhengzhou Chapter in 2019, and the Best Paper Award of the IEEE/CIC ICCC in 2017. He was on the technical program committees of international conferences including IEEE ICC, IEEE GLOBECOM, IEEE WCNC, and CyberC.

Topic: Establish a scientific concept of network security and build a strong defense line of network security

Abstract: This talk will introduce an active immune trusted computing system in order to defend cyberspace vulnerability. This system is designed in a dual computing protection structure that consists of secure and trusted computing nodes, which implement active immune triple-protection supported by the Trusted Security Management Center. It achieves the safety protection such that unauthorized persons cannot obtain sensitive information, the system and its information cannot be changed, and cyber-attacks are immunized maximally. Such a system provides safe and reliable accessibility for users through innovative trusted cryptosystems, innovative active immune system structures, and advanced trusted computing. Trusted computing 3.0 has been successfully applied in 5G backbone networks, national power and other fields.


Biography: Shen Changxiang is an academician of the Chinese Academy of engineering. He graduated from the Department of mathematics of Zhejiang University in 1965. His research interests include military computer information systems, cryptographic engineering, information security architecture, system software security (secure operating systems, secure databases, etc.), network security, etc. He is currently a member of the Standing Committee of the Information and Electronic Engineering Department of the Chinese Academy of Engineering, a member of the State Council Information Technology Expert Advisory Committee, an office consultant of the State Password Management Committee, and the director of the Information Confidentiality Professional Committee of the Chinese Computer Society. He was once awarded the honorary title of “Navy Model Scientific and Technological Worker” and was named a national young and middle-aged expert with outstanding contributions. He has completed more than 20 major scientific research projects and achieved many important results. He has won 2 first prizes, 3 second prizes, 3 third prizes, and more than 10 military science and technology progress awards.

Topic: Wireless Blockchain Networks for COVID-19, 6G, and Automation

Abstract: Originally proposed as the backbone technology of Bitcoin cryptocurrency, blockchain has become a revolutionary decentralised data management framework that can transform the way in which we share information. It offers immutable, transparent, secure and auditable ledger in a trust-less distributed environment, to verify the integrity and traceability of information/assets during their life cycle. Moreover, without a central authority’s involvement, blockchain-enabled smart contracts can significantly reduce manual interventions and thus improve efficiency.
In this talk, wireless blockchain network (WBN), with different network topology and communication protocols, for various commonly used blockchains will be introduced. We will also discover the challenges of WBN, and the relationship between the communication (in terms of spectrum and power provision), and the wireless blockchain network performance (in terms of scalability, throughput and latency, and security). We will try to answer one important question, how much communication resource is needed to run a wireless blockchain network. The talk will present three exemplary use cases we are recently developed: 1), how to use blockchain to achieve privacy-preserving contact tracing APP for COVID-19; 2) how to use blockchain for 5G and beyond spectrum (and computing, power) resource management and sharing; 3), how to use distributed blockchain protocols to achieve high reliable consensus for missing critical industrial IoT and automation.


Biography: Dr. Lei Zhang is a Senior Lecturer (Associate Professor) at the University of Glasgow, U.K. He received his Ph.D. from the University of Sheffield, U.K. His research interests include wireless communication systems and networks, blockchain technology, data privacy and security, radio access network slicing (RAN slicing), Internet of Things (IoT), multi-antenna signal processing, MIMO systems, etc. He has 19 patents granted/filed in more than 30 countries/regions including US/UK/EU/China/Japan etc. Dr Zhang has published 3 books and 100+ peer-reviewed papers. He received IEEE Communication Society TAOS Best Paper Award 2019. He is a Technical Committee Chair of 5th International conference on UK-China Emerging Technologies (UCET) 2020. He was the Publication and Registration Chair of IEEE Sensor Array and Multichannel (SAM) 2018, Co-chair of Cyber-C Blockchain workshop 2019. He is an associate editor of IEEE Internet of Things (IoT) Journal, IEEE Wireless Communications Letters and Digital Communications and Networks. Dr Zhang’s research was widely covered by media including BBC.

Topic: 6G beyond 2030: digital twin, ubiquitous intelligence

Abstract: 5G has been commercialized globally in large scale since 2019. The new era of 'Internet of Everything' has been started, which will stimulate the new demand for improved capabilities of mobile network from the perspective of data rate, efficiency and reliability, etc. These demands will drive the mobile communication evolve towards 6G. Now the research of 6G is still in the stage of vision requirements definition and technical exploration, and the 6G key technical directions are still divergent and far from consensus. With the deep integration of DICT, 6G will fully support the digitization of the world to realize the vision of “digital twin, ubiquitous intelligences”. The twin digital world is the image of the physical world, helping us to further improve the quality of our life and increase the production efficiency. Some typical application scenarios, such as twin body area networks and sensory interconnections related to human development, super smart transportation, holographic communication and intelligent production related to social development, etc., demand higher and more comprehensive network performance indicator requirements for 6G network, such as extremely high reliability, global terrestrial and non-terrestrial 3D coverage, and 2~3 times the spectrum efficiency improvement. With the emergence of new scenarios in the future, 6G network needs more new key performance indicators. The 6G network seems to have several basic features: on-demand fulfillment, lite network, soft network, native AI, native security and digital twin, which will bring innovations to the wireless communication network and realize more efficient and intelligent network development. Network architecture is the cornerstone and framework of the 6G mobile system. We need to further explore it and wish to reach consensus with the industry. So that the future network can be deeply integrated into people's daily life, work and entertainment, empower thousands of industries, and achieve the grand goal of 6G rebuild a new world.


Biography: Dr. Guangyi Liu received his PhD. from Beijing University of Posts and Telecommunications in 2006. He joined China Mobile since 2006, now he is the leading specialist and 6G director of China Mobile Group. Before he joined China Mobile, he has worked for Shanghai Bell and Siemens (Now Nokia) for 3 years. He has led the standardization and industrialization of 4G and 5G in China mobile from 2007 to 2019. Now he is leading the research of 6G. He is also acting as the vice chair of THz and mm-wave industry alliance, and has acted as the chair of spectrum working group and coordinator of 5G eMBB program in Global TD-LTE Initiative (GTI). He has been granted more than 150 patents, and authored and coauthored more than 7 books and published more than 150 papers in IEEE journal and conference.

Topic: Cooperative Security for 5G/6G and the Internet

Abstract: The talk describes the idea of cooperative security for the Internet and 5G/6G. The idea of cooperative security is that all good guys would cooperate automatically to mitigate all hacking over the Internet sharing evidence of misbehaviour, constraining detected infected hosts and deploying security patches as quickly as they become available. The talk outlines the solution called Customer Edge Switching as an implementation of cooperative security. The talk discusses the architecture and describes briefly some use cases under real world constraints. The technical details can be found in www.re2ee.org and naturally e.g. in IEEE Explore. The concepts presented in the talk have been proven by Proof of Concept or running code level experimental implementation published in GitHub/Aalto5G. We encourage it’s use in further experimentation. Our current work is targeted at optimizing the body of running code and learning from use cases in 5G vertical networks.


Biography: Raimo Kantola has a D.Tech degree in computer science from Helsinki University of Technology, Finland. He is a professor in networking technology at department of Comnet, Aalto University, Finland. His research interests include SDN, customer edge switching, trust in networks and cloud security.

Topic: Semantic interoperability for IoT Platforms

Abstract: Recent advances in information and communication technologies include virtualization both at the processing and the communication levels as well as interoperability at the different interaction levels. The progress in networking encompasses Machine-to-Machine (M2M) communications for Internet of Things and Big Data traffic that constitute active research and standardization activities in Europe by ETSI, and around the world by OneM2M. The design and deployment of interoperable IoT platforms based on open systems and interfaces are identified as enablers for the digital market. The strategic application domains include e-heath, connected and automated vehicles, advanced dynamic manufacturing, energy management and smart homes, buildings and cities. IoT Systems provide advantages in all these various domains. This fast-growing ecosystem is leading IoT towards a promising future. However, IoT systems expansion opportunities are not straightforward. A set of challenges should be overcome to enable IoT mass-scale deployment across various domains including interoperability, autonomy, and scalability issues. This talk aims at giving an overview of these challenges. Recent international standardization and R&D initiatives will be investigated. Future directions will be highlighted.


Biography: Khalil DRIRA received the Engineering and M.S. (DEA) degrees in Computer Science from ENSEEIHT (INP Toulouse, France), in 1988. He obtained the Ph.D. and HDR degrees in Computer Science from UPS, University Paul Sabatier Toulouse, France in 1992, and 2005 respectively. He joined CNRS, the French National Center for Scientific Research, in 1993 as a researcher. He is, since Oct 2010, Research Director, a full-time research position at CNRS. Khalil DRIRA’s research interests include formal design, implementation, testing and provisioning of distributed communicating systems and cooperative networked services. He is or has been involved in several national and international projects in the field of distributed and concurrent communicating systems. He is author of more than 150 regular and invited papers in international conferences and journals. He is member of the editorial board of many international journals in the field of software architecture and communicating and distributed systems. Khalil DRIRA has been editor of a number of proceedings, books and journal special issues in these fields.

Topic: Telco’s Digital Transformation & 5G

Abstract: Global telecom market penetration is getting saturated. The industry is facing severe market competition and threats from Internet giants and other OTT players.

FarEasTone, like the most of worldwide leading telco operators, is transforming from a traditional telecom operator to a digital service and enterprise solution provider to open up new economy opportunities. FarEasTone has adopt Big Data analytics , Artificial Intelligence, and Internet of Things (IoT) as core capabilities and competitive advantages. For instance, building up own IoT platform to capture new revenue streams and applying AI technology to fraud detection for revenue loss prevention.

5G as a revolutionary technology is enabling new applications like high quality entertainment services in consumer segment and vertical solutions in enterprise sector, which is becoming the new blue ocean for the telcos.

Biography: Dr. Chee Ching joined FarEasTone in Sep. 2018 as the Chief Transformation Officer and was appointed as the President since Jan. 2019. Her current priority is on the strategy implementation of “Fit, Transform and Grow”, building 5G, Big Data, AI & IoT capabilities, and accelerating FET’s transformation into digital services & advanced ICT Enterprise Solutions provider, beyond traditional telecom services. Chee brought to FarEasTone more than 23 years of rich experience in network operations and IT management in AT&T. Her professional background spans from Network Operations Planning, Systems Engineering, and Process Engineering to Delivering E2E System Solutions for AT&T’s products and services. Chee was awarded Outstanding 50 Asian Americans in Business in 2018 for her distinguished performance.

Topic: Building Secure Cloud Information System using Cloud Security Architecture Tool

Abstract: Todays commercial and government information systems include clouds, networks, data systems, and complex storage databases that contains sensitive personal information. These commercial and government organizations must be entrusted with security and privacy risk management to ensure their information systems operate securely and reliably. In order to provide structured guidance and framework NIST has developed extensive guidelines and specifications to assist organizations. The NIST 800 Series is a set of documents that describe United States federal government computer security policies to implement and manage the system information security risk. For example, SP 800-200 is Cloud Computing Security Reference Architecture specification to accelerate the securely adoption of cloud computing. SP 800-53 R4 defines the security and privacy controls recommended for each functional capability or micro-service a system implements. One of the issues with these standards is how an organization can implement these specifications. To provide this capability, a tool Cloud Security Architecture Tool (CSAT) is developed that aims to leverage the Cybersecurity Framework (CSF) to identify the NIST SP 800-53 security and privacy controls for cloud-based information systems by identifying the necessary functional capabilities the system needs to provide to support the organization's mission and the service the system is designed for. In this talk, we will discuss the motivation and significance of NIST’s specifications. In addition, it provides a discussion on the role of CSAT in an organization to enhance and facilitate adoption of secure cloud solution.

Biography: Anup Kumar ([email protected]) completed his Ph.D. from North Carolina State University and is currently a Professor of CECS Department at the University of Louisville. He is also the Director of Mobile Information Network and Distributed Systems (MINDS) Lab. His research interests include web services, wireless networks, distributed system modelling, and simulation. He has co-edited a book titled, “Handbook of Mobile Systems: Applications ands Services” published by CRC press in 2012. He is an Associate Editor of IEEE Transactions on Services Computing. He is also the Associate Editor of Internal Journal of Web Services Research and International Society of Computers and Their Application Journal. He is a member of IEEE Distinguished Visitor Program (2006-2008). He was the Chair of IEEE Computer Society Technical committee on Simulation (TCSIM) (2004-2007). He has published and presented over 150 papers. Some of his papers have appeared in ACM Multimedia Systems Journal, several IEEE Transactions, Wireless Communication and Mobile Computing, Journal of Parallel and Distributed Computing, IEEE Journal on Selected Areas in Communications etc. He was the Associate Editor of International Journal of Engineering Design and Automation 1995-1998. He has served on many conference program and organizing committees such as IEEE ISCC 2007, IEEE ICSW-2006, IEEE MASS-2005, IEEE SCC-2005, IEEE ICWS-2005, CIT-2005, IEEE MASCOTS, ADCOM 97 and 98. He has also edited special issues in IEEE Internet Magazine, and International Journal on Computers and Operations Research. He is a Senior Member of IEEE.

Topic: Trusted Intelligent Internet of Things: Key Technologies and Application Cases

Abstract: This report introduces the use of blockchain technology to construct a trusted and distributed IoT system architecture to enhance IoT system security and data sharing, which can promote the application value for IoT in future digital economy. Key technologies include device autonomous identity and security authentication, distributed data storage and distribution, and distributed consensus protocol. We will introduce some application cases in intelligent transportation and smart medical care to explore the value of blockchain technology in the real economy.

First, many current critical infrastructures such as power grids, transportation systems, and medicine systems are emerging with the tight integration of physical processes and cyber world. Due to the crucial role of cyber-physical systems in everyday life, cyber-physical security needs to be promptly addressed. Particularly, his research group is focus on the security estimation and control of power grids and industrial control systems. Second, he has a long-term concern on the fundamental networking problem in Internet of Things, such as crowd sensing system, fog computing of intelligence gateway, MIMO wireless technology for smart devices. Particularly, his research group is focus on the sensing, computing, communication, and control integration of Internet of Vehicles (IoV). Third, the long-term view is to develop system intelligence for both CPS and IoT. An emerging trend is data-driven distributed intelligence system. Thus, the large-scale trust and reliable data is the power source for intelligence system. Furthermore, to apply the AI technology (deep learning and computer vision) from the laboratory to the real world that require a new approach to supporting the associated power, weight, space, and real-time constraints. Particularly, his research group is focus on investigating the blockchain technology to construct distributed intelligence system and developing the embedded computer vision and deep learning technology for UAV and autonomous vehicles.

Biography: Chengnian Long is a full professor of Department of Automation, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University. His research interest mainly focuses on the Cyber-Physical Systems (CPS), including: 1) Cyber-Physical Systems (CPS) Security: security estimation and control of CPS, intrusion detection system, blockchain security; 2) Internet of Things (IoT): crowd sensing, fog computing, internet of vehicle, wireless MIMO system and 3) Distributed Intelligence Systems: embedded computer vision for smart devices (UAV, Autonomous vehicles), blockchain.

Topic: AI-enabled Wireless Communication Networks

Abstract: In order to meet the ever-growing requirements of future intelligent applications and services, more and more computing resources and distributed AI algorithms have been deployed in wireless communication networks, thus achieving massive data processing and real-time decision making at local or regional sites. In this talk, we will first introduce the architecture, advantages and future trends of multi-tier computing networks, including the differences and collaborations between cloud, fog, and edge computing technologies. Further, a series of novel AI algorithms and solutions are developed to utilize local and regional computing resources for wireless channel modelling, capacity and coverage optimization, and indoor localization and tracking applications. Our research and experiments reveals the potentials of AI algorithms for wireless communication networks, as well as some new bottlenecks and challenges for future investigation.

Biography: Dr. Yang Yang is currently a full professor with School of Information Science and Technology, ShanghaiTech University, China. Prior to that, he has held faculty positions at The Chinese University of Hong Kong, Brunel University (UK), University College London (UCL, UK), and SIMIT, Chinese Academy of Sciences (CAS, China).

Yang is a member of the Chief Technical Committee of the National Science and Technology Major Project "New Generation Mobile Wireless Broadband Communication Networks" (2008-2020), which is funded by the Ministry of Industry and Information Technology (MIIT) of China. In addition, he is on the Chief Technical Committee for the National 863 Hi-Tech R&D Program "5G System R&D Major Projects", which is funded by the Ministry of Science and Technology (MOST) of China. Yang is a General Co-Chair of IEEE DSP 2018 conference and a TPC Vice-Chair of IEEE ICC 2019 conference.
Yang's current research interests include wireless sensor networks, Internet of Things, Fog computing, Open 5G, and advanced wireless testbeds. He has published more than 200 papers and filed over 80 technical patents in wireless communications. He is a Fellow of the IEEE.

Topic: Optimal Network Decomposition for Next-Generation Mobile Communication Systems

Abstract: The fundamental idea of network decomposition is to break a large-scale network into smaller parts such that the subnetworks can operate in parallel, each with a much lower dimensionality. For large-scale wireless networks, the cellular structure is based on the idea of network decomposition, where the network is decomposed into multiple subnetworks, i.e., cells, according to the coverage of each base-station (BS). Such a decomposition scheme, nevertheless, leads to strong interference among subnetworks, which becomes increasingly significant as the density of BSs grows. For the next-generation cellular network where a massive amount of BSs need to be deployed to meet the ever-increasing demand of high data rate, it is of paramount importance to develop efficient network decomposition schemes to replace the current cellular structure. How to build such a decomposition framework, unfortunately, has remained largely unknown.

In this talk, I will introduce our recently proposed network decomposition theory for large-scale wireless networks. Specifically, starting from a novel bipartite graph representation of an infrastructure-based wireless network, I will show that in general the optimal network decomposition can be formulated as a graph partitioning problem. I will then demonstrate how to solve it by the proposed Binary Search based Spectral Relaxation (BSSR) algorithm. The performance of the proposed BSSR algorithm is further examined and compared to the current cellular structure and BS clustering in various scenarios. Significant gains are shown to be achieved by the proposed BSSR algorithm, which corroborates that the optimal network decomposition of next-generation cellular networks should be performed based on a bipartite graph where the geographical information of BSs and users are both included.

Biography: Dr. Lin Dai received the B.S. degree from Huazhong University of Science and Technology, Wuhan, China, and the M.S. and Ph.D. degrees from Tsinghua University, Beijing, China, all in electronic engineering. She is now a full professor of Department of Electronic Engineering of City University of Hong Kong.

She has broad interests in communications and networking theory, with special interests in wireless communications. Her recent research work focuses on modeling, performance analysis and optimal access design of next-generation mobile communication systems.

She was a co-recipient of the Best Paper Award at the IEEE Wireless Communications and Networking Conference (WCNC) 2007 and the IEEE Marconi Prize Paper Award (the annual Best Paper Award of IEEE Transactions on Wireless Communications) in 2009. She received The President's Award of City University of Hong Kong in 2017.

Topic: Blockchain Data Sharing and Its Industry Case Study

Abstract: Due to the advanced features of openness, anonymity, immutability and decentralization of blockchain technology, it is currently a hot topic of interest to technology giants and business communities. Combining with big data, cloud computing and IoT, blockchain technology is a promising trend and is expected to ensure sharing data trustworthiness and security. Using the smart contract and distributed storage in blockchain to reduce costs, improve work efficiency and promote social development of the intelligent.

This talk will introduce disadvantages of traditional centralized data and definite advantages brought by blockchain in data sharing. Furthermore, we will propose the application of blockchain data sharing in different industries in detail, such as agriculture, IoT, medical health and so on. Especially, framework design, smart contracts and consensus mechanisms give our own methods. At last, we will talk about the point that blockchain promotes coordinated social development and shared economy.

Biography: Dr. Guangxia Xu is a Professor, PhD Tutor, and the Vice Dean of Academy of Advanced Interdisciplinary Research at Chongqing University of Posts and Telecommunications, Chongqing, China. She is a senior member of China Computer Federation (CCF) and Blockchain Committee member of CCF, IEEE senior member and ACM member. She received his B.S., M.S., and Ph.D. degree in Computer Science and Technology from Chongqing University, Chongqing, China in 2000, 2006, and 2011 respectively. She was a visiting scholar at Stevens Institute of Technology, New Jersey, USA and a post-doctor at School of Communication and Information Engineering, Chongqing University. She is honored as "The leading talents of the scientific and technological innovation" in Chongqing.

Prof. Xu's research interests include network security, blockchain security, intelligent security, and intrusion detection and data fusion. She authored over 60 journal and conference papers in such areas. As a project leader, she has managed a number of projects from the National Natural Science Foundation of China, National Key Research and Development Plan, etc. She won 1st prize in 2013 and 2nd prize in 2016 for the Science & Technology Progress Award from the Chongqing City Government. She has served as a member of the editorial board of the Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition) and as a reviewer of IEEE Internet of Things, ACM Computing Surveys, Digital Communications and Network, Journal of Network and Computer Applications.

Topic: Cyber-Physical Approach to Resilient City-Scale IoT Systems

Abstract: With the increasing connectivity and intelligence of massive objects, various city-scale systems such as utility infrastructures and transportation systems are evolving into their next generations for higher efficiency. However, they also face growing risks such as unexpected disturbances and even malicious attacks. Therefore, in the pursuit of the smart city vision, it is also important to enhance the resilience of these systems upon the contingency of these risks. In this talk, I will present our recent research on leveraging a city-scale physical process, i.e., the delivery of alternating current electricity, to achieve resilient timestamping and clock synchronization for Internet-of-Things objects found in electrified systems, smart ambient, and even on human bodies.

Biography: Dr. Rui Tan is an Assistant Professor at School of Computer Science and Engineering, Nanyang Technological University. Previously, he was a Senior Research Scientist at Advanced Digital Sciences Center, a Singapore-based research center of University of Illinois at Urbana-Champaign, and a postdoctoral Research Associate at Michigan State University. He received PhD degree from City University of Hong Kong. His research interests include sensor networks, Internet of things, and cyber-physical systems. He is the recipients of IPSN'17 and CPSR-SG'17 Best Paper Awards, IPSN'14 and PerCom'13 Best Paper Award Runner-Ups, and CityU Outstanding Academic Performance Award. He is a Senior Member of the IEEE.

Topic: Ubiquitous Network - From Terrestrial To Aerospace

Abstract: The Phase 1 5G NR standardization (Rel.15) has been frozen in 3GPP by March 2019, which mainly focused on the traditional eMBB services. In later releases, the standardization society envisions more vertical applications from the scoping of the work items, such as V2X, NR-U, Industrial IoT, NR-light, NTN, AR/VR, home-IoT. The 5G-beyond or 6G vision is aimed to provide a ubiquitous and robust network, where mobile terminals could be anywhere and access the network at any time. This cannot be fulfilled solely based on the traditional cellular networks, but also rely on the non-terrestrial operators such as satellite and HAPS (e.g., drones or hot-air balloon). This talk briefly introduces the latest standardization activities in 3GPP, and focus more on the use case and technical challenges of non-terrestrial networks.

Biography: Dr. Li Tian is currently a research manager at the department of the wireless algorithm of ZTE corporation. He received his bachelor degree in Communication Engineering and the Ph.D. degree in Control Science and Control Engineering from Tongji University, Shanghai, China. He was a visiting Ph.D. student at the Department of Electronics and Information Systems (DEIS) of University of Bologna from 2013 to 2014. His current research interests are in the field of 5G new radio access technology, with over 40 scientific papers, 200 standard contributions, and 30 globally filed patents. He is a 3GPP RAN delegate and serve as rapporteur of Rel.16 Two-step RACH WI.

Topic: When Telecom Network Meets Neural Network

Abstract: Network Intelligence lately has been a luring concept that network operators, vendors, and researchers all are passionate about. Deep neural network is the main stream architecture of the state-of-art artificial intelligence technologies across a number of disciplines such as image processing, speech recognition, natural language understanding, etc. What is the potential of a deep neural network for a telecom network? This talk overviews the recent industrial and academic efforts on this line of exploration and shares the challenges.

Biography: Dr. Feng has led R&D of China Mobile on artificial intelligence and big data since September 2013. She had been the architect of IBM Big Data from January 2013.1 to August 2013 and a principal researcher at AT&T Labs Research from August 2001 to January 2013. Dr. Feng received her Ph.D. on Speech Recognition in 2001 from Chinese Academy of Sciences. She is an IEEE senior member, an IEEE speech and language committee member and IEEE industry committee member. She is a reviewer for major data mining, speech, and natural language international conferences and journals. She has chaired and organized multiple conferences in these fields. Dr. Feng has over 70 professional publications and has been granted 42 U.S and international patents.

Topic: On the Security of Smart Contract

Abstract: Smart Contracts are driving BlockChain Application into a much wider area. It embeds business logic into BlockChain systems as automatic execution of computer programs. The execution is imperative and is immune to external intervention. While the mechanism is to implement trusted online compromise on BlockChain, the design and execution of smart contract ode are still subject to various riskes. Investigation of the security of smart contracts, both before deployment and after deployment, are extremely important. This talk shares the exploration on the security of smart contracts before deployment. The exploration takes on the perspective of security testing and exploit testing techniques to understand the potential security risks of smart contracts.

Biography: Dr. Gansen Zhao received his Ph.D from the University of Kent, UK. He had worked for Oracle UK before his academic career. After serving for 2 years for Sun Yat-sen University, Dr. Zhao has been serving as a full professor in School of Computer Science, South China Normal University, China. He is now the deputy dean of School and is leading the Key Lab on Cloud Security and Assessment Technology of Guangzhou.His main research interests include Cloud Security, Trust Management, and BlockChains. He has published extensively in the above areas, and serves as program chairs for a number of conferences.

Topic: Novel Cryptanalysis and Design of Symmetric Ciphers

Abstract: As the cornerstone to assure cybersecurity, the cipher plays a critical role in the security authentication and encipherment protection. With the advantage of high efficiency, the symmetric-key encryption scheme has a broader and more flexible application comparing to the public-key encryption scheme. This report is centred on the design and cryptanalysis of symmetric ciphers. On the aspect of automatic cryptanalysis, we manage to depict the problems in cryptography from the view of operational research and algebraic theory. A series of automatic models regarding different kinds of attack methods are constructed, which become valuable universal analytical tools in the international cryptology field. These new models are integrated into the platform of automatic cryptanalysis, which can efficiently accomplish the tasks in cryptanalysis and plays a crucial part in the design of innovative ciphers. The design and cryptanalysis of ciphers are two complementary sides and bring out the best in each other. Thus, the update of cryptanalytical methods also promotes the development of design techniques. We transform powerful analytical methods into ingenious design techniques and design several novel symmetric ciphers.

Biography: Meiqin Wang takes charge of Executive Vice-President of School of Cyber Science and Technology, Shandong University and Vice-Director of Key Laboratory of Cryptologic Technology and Information Security, Ministry of Education, Shandong University. Supported by the 973 Program, National Natural Science Foundation of China, and Chinese Major Program of National Cryptography Development Foundation, she mainly studies cryptanalysis and design methods of the symmetric cipher. In recent years, she has published more than 60 papers in top conferences and journals of cryptography, including 13 papers in the top 5 international conferences. She was invited to give talks on many international seminars of cryptography, such as the Dagstuhl Seminar on Symmetric Cryptography, Early Symmetric Cryptography (ESC), and Asian-workshop on Symmetric Key Cryptography (ASK). She is a member of a council for the Chinese Association for Cryptologic Research. As a co-chair, she held the third Asian-workshop on Symmetric Key Cryptography. She undertook the program chairs of several top 5 international conferences in the field of cryptography, such as ASIACRYPT and FSE.

David Lu , Vice President, SDN Platform & Systems, is responsible for development and engineering of AT&T’s next generation SDN (Software Defined Network) platform enabling AT&T network virtualization and OSS/operation process transformation which includes ECOMP platform and open source ECOMP (ONAP), API, micro-services, policy control & orchestration, hyper-automation, and advanced data analytics. David leads a multifaceted organization with more than 3,000 people across the globe.

David is a well-respected leader across multiple technology domains including: large scale, real time software architecture and development, network performance and traffic management, work flow and policy-controlled automation, large database and big data implementation (mining & analytics), machine learning, artificial intelligence, software reliability and quality, and network operations process engineering. David has led major software platform transformation initiatives from sales to network/service delivery/assurance, and billing platforms. Examples of his David’s achievements include large scale platforms he has both led and engineered that process annually: 984 Trillion Trillion network performance events and 348 Billion alarms with 99.99%+ automation; 60 Million dispatches with 14.4 Billion automated manual steps; and over 90 Billion API transactions.

Since joining AT&T Bell Labs in 1987, David has served in various leadership positions at AT&T. Over the past 15 years, David has led numerous automation initiatives that have resulted in multi-billion-dollar savings and in 2010 he received the CIO 100 Award for his efforts. David holds 45 patents and has frequently appeared as a guest speaker at technical and leadership seminars and conferences throughout the world. David has received numerous industry awards including the 2015 Chairman’s Award from the IEEE Communication Society for Network and Systems Quality and Reliability; and the 2017 CIE AAEOY (Asian America Engineer of Year) Award . David is tremendously active in community organizations and activities including AT&T APCA, DFW-CIE, the DFW Asian American Chamber of Commerce, and was recognized by AT&T APCA in 2015 with the Corporate Leadership Award .

David was accepted to the world-renowned Shanghai Conservatory of Music and came to the U.S. to complete his college education; an undergraduate degree in Music (majoring in cello performance), and a graduate degree in Computer Science.