The 2022 Annual ShanghaiTech Symposium on Information Science and Technology
(ASSIST 2022)

The 2022 Annual ShanghaiTech Symposium on Information Science and Technology
(ASSIST 2022)

27-28 August 2022, Shanghai, China

27-28 August 2022, Shanghai, China


Program

Keynote Speakers

Jianwei Huang

Chinese University of Hong Kong, Shenzhen

Dean of the School of Science and Engineering
Vice President of Shenzhen Institute of Artificial Intelligence and Robotics for Society
Editor-in-Chief of IEEE Transactions on Network Science and Engineering
IEEE Fellow
AAIA Fellow
Speech detail

Fred C. Lee

Center for Power Electronics Systems (CPES), Virginia Tech

University Distinguished Professor Emeritus
Founder and Director Emeritus of CPES
National Academy of Inventors (NAI) Fellow
IEEE Fellow
Speech detail

Liye Xiao

Institute of Electrical Engineering of Chinese Academy of Sciences

Professor
Speech detail

Confirmed Speakers

Lap-Pui Chau

Department of Electronic and Information Engineering, Hong Kong Polytechnic University

IEEE Fellow
Professor
Speech detail

Xu Chen

Sun Yat-sen University

Assistant Dean at School of Computer Science and Engineering
Professor
Speech detail

Nan Cheng

School of Telecommunications Engineering, Xidian University

Professor
Speech detail

Masahiro Fujita

The University of Tokyo

Head of AI Chip Design Open Innovation Laboratory (AIDL), National Institute of Advanced Industrial Science and Technology (AIST), Japan
Retired Professor, The University of Tokyo
Speech detail

 

Yue Gao

Fudan University

Professor
Speech detail

Jianye Hao

Tianjin University

Professor
Director of Huawei Noah's Ark Decision-making and Reasoning Lab
Speech detail

Longbo Huang

Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University

Professor
Speech detail

Adrian Ioinovici

Holon Institute of Technology, Nanjing University of Aeronautics and Astronautics

Professor
IEEE Fellow
Speech detail

 

Bin Li

School of Electrical and Information Engineering, Tianjin University

Executive Vice Dean, Graduate School of Tianjin University
Professor
Speech detail

Hong Li

School of Electrical Engineering, Beijing Jiaotong University

Professor
Speech detail

Wuhua Li

College of Electrical Engineering, Zhejiang University

Vice Dean
Professor
Speech detail

Teng Long

Cambridge University

Professor
Speech detail

 

Arokia Nathan

Darwin College, University of Cambridge

IEEE Fellow
Professor
Speech detail

Xinbo Ruan

Department of Electric Engineering, Nanjing University of Aeronautics and Astronautics

IEEE Fellow
Professor
Speech detail

Guobing Song

School of Electrical Engineering, Xi'an Jiaotong University

Professor
Speech detail

Zhou Su

Xi'an Jiaotong University

Dean of School of Cyber Science and Engineering
Professor
Speech detail

 

Yongwen Wang

National University of Defense Technology

Professor
Speech detail

Minghao Wen

School of Electrical and Electronic Engineering, Huazhong University of Science and Technology

Professor
Speech detail

Yuedong Xu

School of Information Science and Technology, Fudan University

Professor
Speech detail

Xu Yang

School of Electrical Engineering, Xi'an Jiaotong University

Vice Dean at School of Electrical Engineering Professor
Professor
Speech detail

 

Yang Yu

School of Artificial Intelligence, Nanjing University

Professor
Speech detail

Zhengming Zhao

Department of Electric Engineering, Tsinghua University

IEEE Fellow
Professor
Speech detail

Haibo Zhou

School of Electronic Science and Engineering, Nanjing University

Professor
Speech detail

Ting Zhou

Shanghai Advanced Research Institute, CAS

Professor
Speech detail

 

Chunbo Zhu

School of Electrical Engineering, Harbin Institute of Technology

Professor
Speech detail

Haojin Zhu

Shanghai Jiao Tong University

Professor
Speech detail

 

 

 

 

Speakers and Speeches Information

Lap-Pui Chau

Department of Electronic and Information Engineering, Hong Kong Polytechnic University

Title: Image Analytics Using Surveillance Camera

Abstract:  Image analytics using roadside surveillance camera becomes a research focus in recent years. Roadside surveillance camera will generate a large amount of data. These data will contain important information on the application of smart cities and transportation systems, which makes the daily operation safer, more efficient, and greater user satisfaction. Various vision based roadside sensors such as surveillance video camera and IR camera are used to achieve these tasks. In this talk, we will discuss the image analytics used for various applications.

Bio:  Lap-Pui Chau received the Ph.D. degree from The Hong Kong Polytechnic University in 1997. He was with School of Electrical and Electronic Engineering, Nanyang Technological University from 1997 to 2022. He is currently a Professor in the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University. His research interests include visual signal processing, light-field imaging, computer vision, video analytics for intelligent transportation system, and human motion analysis. He is an IEEE Fellow. He was the chair of Technical Committee on Circuits & Systems for Communications of IEEE Circuits and Systems Society from 2010 to 2012. He was general chairs and program chairs for some international conferences. Besides, he served as associate editors for several IEEE journals and Distinguished Lecturer for IEEE BTS.

Xu Chen

Sun Yat-sen University

Title: Enabling Real-Time Deep Graph Inference with Fog Computing

Abstract:  Graph Neural Networks (GNNs) have gained growing interest in miscellaneous applications owing to their outstanding ability in extracting latent representation on graph structures. To render GNN-based service for IoT-driven smart applications, the traditional model serving paradigm resorts to the cloud by fully uploading the geo-distributed input data to the remote datacenter. However, our empirical measurements reveal the significant communication overhead of such cloud-based serving and highlight the profound potential in applying the emerging fog computing. To maximize the architectural benefits brought by fog computing, in this talk, we present Fograph, a novel distributed real-time GNN inference framework that leverages diverse resources of multiple fog nodes in proximity to IoT data sources. By introducing heterogeneity-aware execution planning and GNN-specific compression techniques, Fograph tailors its design to well accommodate the unique characteristics of GNN serving in fog environment.

Bio:  Dr. Xu Chen is currently a Full Professor and Assistant Dean at School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China. He obtained the Ph.D. degree in Information Engineering from The Chinese University of Hong Kong, Hong Kong, China. Dr. Chen was a Postdoctoral Research Fellow with Arizona State University, USA, and a Humboldt Scholar Fellow with Institute of Computer Science of University of Goettingen, Germany. Dr. Chen has published over 150 scientific papers in leading international conferences and journals, many of which appear in top-tier conferences such as MOBIHOC, ICDCS and INFOCOM and top-tier journals such as IEEE JSAC, IEEE TON and IEEE TMC. He received 2020 IEEE Computer Society Best Paper Awards Runner-up , 2017 IEEE Communication Society Asia-Pacific Outstanding Young Researcher Award, 2017 IEEE ComSoc Young Professional Best Paper Award, Honorable Mention Award of 2010 IEEE international conference on Intelligence and Security Informatics (ISI), Best Paper Runner-up Award of 2014 IEEE International Conference on Computer Communications (INFOCOM), and Best Paper Award of 2017 IEEE International Conference on Communications (ICC). He currently serves as an area editor for IEEE Open Journal of the Communications Society, and associate editors for IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, and IEEE Internet of Things Journal. He also serves as TPC members for a series of top tier conferences including MOBIHOC and INFOCOM.

Nan Cheng

School of Telecommunications Engineering, Xidian University

Title: On-Demand Resource Allocation for Wireless Networks Based on Dynamic Neural Models

Abstract:  The evolution and development of 6G networks introduce distinctive and personalized scenarios and services with diverse requirements, which pose great challenges on the orchestration of network resources. Although the resource allocation method based on deep learning reduces the decision delay, its inference capability and computational cost are fixed, making it difficult to adapt to the network environment and service requirements. In this report, according to the dynamic environment and service requirements, an adaptive network resource allocation decision method based on dynamic neural models is proposed. Dynamic neural network (DyNN) is a novel neural network model with variable structure. During inference, the model hyper-parameters (such as number of layers, width and path) can be dynamically adjusted according to the input, which makes it applicable to dynamic demands, heterogeneous networks, energy constraints and other scenarios. This report focuses on two common wireless network tasks, multi-user transmission and edge task offloading, and discusses the design ideas, implementation methods, and simulation results of the network orchestration decision methods based on dynamic neural models. Considering the model inference time in the total delay and training the dynamic neural model accordingly, the inference delay and accuracy can be adjusted on demand to meet different service requirements and environments.

Bio:  Nan Cheng received the Ph.D. degree from the Department of Electrical and Computer Engineering, University of Waterloo in 2016, and B.E. degree and the M.S. degree from the Department of Electronics and Information Engineering, Tongji University, Shanghai, China, in 2009 and 2012, respectively. He worked as a Post-doctoral fellow with the Department of Electrical and Computer Engineering, University of Toronto, from 2017 to 2019. He is currently a professor with State Key Lab. of ISN and with School of Telecommunications Engineering, Xidian University, Shaanxi, China. He has published over 70 journal papers in IEEE Transactions and other top journals. He serves/served as guest editors for several journals and serves as associate editors for IEEE Transactions on Vehicular Technology, IEEE Open Journal of the Communications Society, and Peer-to-Peer Networking and Applications. His current research focuses on B5G/6G, space-air-ground integrated network, big data in vehicular networks, and self-driving system. His research interests also include applying AI techniques for future networks.

Masahiro Fujita

The University of Tokyo

Title: Parallel Scheduling Modern Deep Learning Implementations: Synthesis and Generalization of Parallel Algorithms Considering Communication Constraints

Abstract:  We discuss parallel scheduling methods targeting various deep learning computation on top of parallel computing environments. The assumed parallel computing environments are based on many processing elements with ring connections or two-dimensional mesh connections as examples of targets. These are easy to implement architectures, and hence they can be utilized in various AI system integration. We first discuss the problems of dense matrix-vector multiplications and its extension to convolutional neural networks. Our approach has three steps. In the first step, small instances of the parallel scheduling problem are formulated as SAT problems and are optimally solved. In the second step, general scheduling algorithms which works for any sizes of problems are interactively inferred with our template based synthesis methods. In the third and final step, the correctness of the synthesized scheduling algorithms is formally verified. The proposed method has also been applied to the cases of sparse matrices and self-attention which is now one of the hottest topics in the field as well as Convolution Neural Network (CNN) inference engine on FPGA. For these cases as well, we have come up with the general parallel scheduling algorithms which have been proven to be very close to the optimum ones through experiments.

Bio:  Masahiro Fujita received his Ph.D. in Information Engineering from the University of Tokyo in 1985, and joined Fujitsu. Since March 2000, he has been a professor at VLSI Design and Education Center of the University of Tokyo until he retired in March, 2022. He is now working at National Institute of Advanced Industrial Science and Technology (AIST), Japan. He has done innovative work in the areas of hardware verification, synthesis, testing, and software verification-mostly targeting embedded software and web-based programs. He has authored and co-authored 12 books, and has more than 300 publications. He has been involved as program and steering committee member in many prestigious conferences on CAD, VLSI designs, software engineering, and more. His current research interests include synthesis and verification in SoC (System on Chip) especially for AI applications, hardware/software co-designs targeting embedded systems, digital/analog co-designs, and formal analysis, verification, and synthesis of web-based programs and embedded programs.

Yue Gao

Fudan University

Title: Space-Air-Ground Integrated Network for 6G

Abstract:  The space-air-ground integrated network (SAGIN) aims to provide seamless wide area connections, high throughput and strong resilience for B5G and 6G communications. Acting as a crucial link segment of the SAGIN, unmanned aerial vehicle (UAV)-satellite communication has drawn much attention. However, it is a key challenge to track dynamic channel information due to the low earth orbit (LEO) satellite orbiting and three-dimensional (3D) UAV trajectory. This presentation will outline the current development and key challenges of SAGIN including GSO, MEO, LEO satellite, Starlink and 5G NR 3GPP non-terrestrial network (NTN). Some key technologies such as 3D channel tracking between UAV and satellite, and between UAV and ground terminals, beamforming, beam tracking and learning as well as wideband compressive sensing and learning will be briefly introduced.

Bio:  Yue Gao is a Professor at School of Computer Science, and Director of Intelligent Networking and Computing Research Centre at Fudan University. He received the Ph.D. degree from the Queen Mary University of London (QMUL) U.K., in 2007. He has then worked as a Lecturer, Senior Lecturer, Reader and Chair Professor at QMUL and University of Surrey, respectively. His research interests include smart antennas, sparse signal processing and cognitive networks for mobile and satellite systems. He has published over 200 peer-reviewed journal and conference papers and over 5700 citations. He was a co-recipient of the EU Horizon Prize Award on Collaborative Spectrum Sharing in 2016 and elected as an Engineering and Physical Sciences Research Council Fellow in 2017. He is a member of the Board of Governors and Distinguished Lecturer of the IEEE Vehicular Technology Society (VTS), Vice-Chair of the IEEE ComSoc Wireless Communication Technical Committee, past Chair of the IEEE ComSoc Technical Committee on Cognitive Networks. He has been an Editor of several IEEE Transactions and Journals, and Symposia Chair, Track Chair, and other roles in the organising committee of several IEEE ComSoC, VTS and other conferences.

Jianye Hao

Tianjin University

Title: Self-supervised Reinforcement Learning

Abstract:  Reinforcement learning has achieved great success in recent years but still suffers from sample efficiency and scalability issues, which significantly limits the wide application of RL to real application scenarios. One of the major bottlenecks of RL is the limited representation power in terms of the key components of RL including states, policies, actions and environments. In this talk, I will introduce how to leverage self-supervised techniques to increase the representation power of RL from different aspects of RL to boost the learning efficiency and scalability across different scenarios and tasks, and also discuss the path towards pre-trained big decision-making model in the future.

Bio:  Dr. Jianye Hao is Associate Professor at Tianjin University and Director of Huawei Noah's Ark Decision-making and Reasoning Lab. His research area focuses on reinforcement learning and multiagent systems. Dr. Hao has published over 100 peer-reviewed papers in top conferences and journals and won a number of best paper awards such as ASE2019 and CoRL2020, and champions of a number of international competitions at NeurIPS 20-21. The research of his team has been successfully applied in various domains such as Game AI, E-commerce recommendation, network optimization, supply chain optimization and so on.

Jianwei Huang

Chinese University of Hong Kong, Shenzhen

Title: AI-Aided Low Carbonization Research

Abstract:  This talk will provide an overview of our latest research regarding how to use AI technologies to accelerate the process of achieving the national strategy goals of carbon peaking and carbon neutrality goals. The discussions will focus on the energy and transportation sectors, as well as recent efforts of improving carbon measurement and carbon trading.

Bio:  Jianwei Huang is a Presidential Chair Professor and Associate Dean of the School of Science and Engineering, the Chinese University of Hong Kong, Shenzhen. He also serves as Vice President of Shenzhen Institute of Artificial Intelligence and Robotics for Society, and the Editor-in-Chief of IEEE Transactions on Network Science and Engineering. He received the Ph.D. degree in ECE from Northwestern University in 2005, and worked as a Postdoc Research Associate in Princeton University during 2005-2007. From 2007 until 2018, he was on the faculty of Department of Information Engineering, the Chinese University of Hong Kong. His research interests are in the area of network optimization, network economics, and network science, with applications in communication networks, energy networks, data markets, and crowd intelligence. He has published more than 300 papers in leading venues, with a Google Scholar citation of 14900+ and an H-index of 61. He has co-authored 11 Best Paper Awards, including the 2011 IEEE Marconi Prize Paper Award in Wireless Communications. He has co-authored seven books, including the textbook on "Wireless Network Pricing." He is an IEEE Fellow, an AAIA Fellow, an IEEE ComSoc Distinguished Lecturer, a Clarivate Web of Science Highly Cited Researcher, and a Chang Jiang Distinguished Professor.

Longbo Huang

Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University

Title: Regularization, Softmax and Zeroth-order Optimization for Multi-Agent Reinforcement Learning

Abstract:  Deep reinforcement learning (DRL) has received much attention and finds successful applications in various important fields, including games, robotics, transportation and science. Despite its continuing success, DRL still faces several major challenges, including accurate value function estimation, improved sample efficiency and efficient practical implementation. In this talk, we will present our recent results on tackling these issues in multi-agent DRL (MARL). (i) Using regularization and Softmax for efficient policy search in MARL. We first discover a gradient explosion issue suffered by existing methods, which severely affects value function estimation. We then propose a novel Softmax and regularization-based update scheme RES to penalizes large joint action-values that deviate from a baseline and demonstrate its effectiveness in policy learning. (ii) Developing efficient algorithms for offline MARL with conservatism and zeroth-order methods. We showed that existing algorithms such as CQL and TD3-BC can be inefficient in MARL. Then, we propose Offline Multi-Agent RL with Actor Rectification (OMAR), which combines the first-order policy gradients and zeroth-order optimization methods to better optimize the conservative value functions over the actor parameters.

Bio:  Dr. Longbo Huang is an associate professor (with tenure) at the Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University, Beijing, China. Dr. Huang’s research focuses on AI for Decisions. He serves/served on 50+ TPCs and 10+ organizing committees for ACM/AI/IEEE conferences, including the General Chair for ACM Sigmetrics 2021, the TPC co-chair for ITC 2022, WiOpt 2020 and NetEcon 2020. Dr. Huang serves on the editorial board for ACM ToMPECS and IEEE/ACM ToN. He is a senior member of ACM and IEEE, an IEEE ComSoc Distinguished Lecturer, and an ACM Distinguished Speaker. Dr. Huang received the Outstanding Teaching Award from Tsinghua University in 2014, the Google Research Award and the Microsoft Research Asia Collaborative Research Award in 2014, and was selected into the MSRA StarTrack Program in 2015. Dr. Huang won the ACM SIGMETRICS Rising Star Research Award in 2018.

Adrian Ioinovici

Holon Institute of Technology, Nanjing University of Aeronautics and Astronautics

Title: Line - Load Common Ground Switched-capacitor Multilevel Inverters (SCMLI)

Abstract:  The multilevel inverters (MLI) replaced the two-level inverters owing to their capacity to provide a staircase waveform much closer to a perfect sinusoid. The use of switched-capacitor cells in MLI instead of inductor-capacitor components brought higher power density and automatic balancing of the capacitor voltages. For photovoltaic supplied systems, the main problem is the leakage current of the solar cells, which seriously diminish the efficiency . The realization of a common ground between the input source and the grid neutral reduces this current to zero. The talk will present the basic topologies in SCMLIs, with and without output bridge , including solutions with one input source and with multiple symmetrical and asymmetrical input sources, and basic modulations: NLC ( near level corner) and SPWM. Then, it will be explained how a line-load common ground could be obtained in these inverters at the cost of losing an important feature in inverters supplied by renewable sources:  a continuous input current. The newest state-of-the art common-ground SCMLI with continuous input current and  minimal number of SC cells per boost factor will be discussed in detail.

Bio:  Adrian Ioinovici is a Chair professor with Holon Institute of Technology, Israel. In the last decade, within the P R China "one thousand experts" program,  he served as a professor and Director of the Power Electronics Center at the Sun Yat-sen University , Guangzhou, and then as a Professor at the Nanjing University of Aeronautics and Astronautics. He serves as an Associate Editor for IEEE Trans. on Power Electronics and IEEE Trans. on Industrial Electronics , and as a Co-Editor - in - Chief of WSEAS Transactions on Advances in Engineering Education. He acted as a Guest Editor for many special issues of IEEE Trans. on CAS, IEEE Trans. on IE, and in the Journal of Circuits, Systems , and Computers.  Dr. Ioinovici presented tutorials or key-note speeches at many international conferences. He served in many years as a member of the IEEE Fellows Committee. Prof. Ioinovici is the author of the books: Computer-Aided Analysis of Active Circuits ( M. Dekker, New York) and Power Electronics and Energy Conversion Systems ( J.Wiley @Sons Ltd.), which was translated to Chinese in 2017 by Publishing House of Electronics Industry ( Beijing). He also authorized 200 IEEE journals and conference papers. Dr. Ioinovici pioneered the Switched Capacitor Power Electronics, for which he was promoted to IEEE Fellow. His present research is focused on switched-capacitor converters and multilevel inverters , large dc gain converters, and soft-switching power electronics circuits.

Fred C. Lee

Center for Power Electronics Systems (CPES), Virginia Tech

Title: Powering the Next Generation of Microprocessor

Abstract:  Recent advancements of CPU, GPU and AI by adopting the multi-core parallel processing, have demonstrated performance improvements at a rate beyond Moore’s Law. For example, the new generation of GPU has grown into 600 cores and demands 1000 amperes of current. This rather dramatic change in processor technology has imposed significant challenge to the power delivery and management. The current form of Data center power architecture with 12V voltage regulators (VRs) has been replace with 48V VRs, with significant impact in the overall system efficiency. With the advent of the new generation of wide bandgap power semiconductor devices, the authors propose a design practice that marks a significant departure from the current practice. Simultaneous improvements in efficiency, power density, EMI are demonstrated with potential impact on manufacturing paradigm and cost. The author will further share some thoughts on more advanced power architecture beyond the current main-stream development activities.

Bio:  Fred C. Lee received his B.S. degree in electrical engineering from the National Cheng Kung University in Taiwan in 1968, and his M.S. and Ph.D. degrees in electrical engineering from Duke University in 1972 and 1974, respectively. Dr. Lee is a University Distinguished Professor Emeritus and Founder and Director Emeritus of CPES, a preeminent academic center in power electronics research at Virginia Tech. As CPES Director, Dr. Lee leads a program that encompasses research, technology development, educational outreach, industry collaboration, and technology transfer. CPES focuses its research to meet industry needs and allows industry to profit from the Center's research and outputs. The CPES program enables its Principal Plus industry members to sponsor graduate fellowships and provides the opportunity to direct research in areas of mutual interest, as well as the ability to access intellectual properties generated collectively by all industry-funded fellowships on a royalty-free and non-exclusive basis. To date, more than 230 companies worldwide have benefited from the industry partnership program. The center has been cited by NSF as a model ERC for its industry collaboration and technology transfer, education, and outreach programs. Dr. Lee's research interests include high-frequency power conversion, magnetics and EMI, distributed power systems, renewable energy, power quality, high-density electronics packaging and integration, and modeling and control. Dr. Lee holds 89 U.S. patents, and has published 310 journal articles and 740 refereed technical papers. During his tenure at Virginia Tech, Dr. Lee has supervised to completion 87 Ph.D. and 93 Master's students. According to Microsoft H index, Dr. Lee is rated among the top three best cited authors for over 2.5 million engineering authors in the world.

Bin Li

School of Electrical and Information Engineering, Tianjin University

Title: Fault Analysis and Protection Principles for Hybrid Multi-Terminal DC Systems

Abstract:  Large capacity long distance AC/DC transmission techniques and engineering applications are vital for optimal dispatch of energy resources in China. With the technical developments and engineering requirements, the research and practice of hybrid multi-terminal DC systems are inevitable trends of power grid evolvement and transformation. It is essential to study and solve the following scientific and technical issue: how to ensure survivability of the hybrid multi-terminal DC system during faults. This presentation will analyze, elaborate and discuss the fault impacts, control schemes and protection principles for hybrid multi-terminal DC systems

Bio:  Prof. Bin Li a Professor in Tianjin University and the Executive Vice Dean of Graduate School of Tianjin University. He is the recipient of the Distinguished Young Scholars of National Natural Science Foundation of China (NSFC), and the recipient of National Millions of Talents Project, and the director of Tianjin Key Laboratory of Power System Simulation and Control. His research interests include protection and control of smart grids. He has published over 90 SCI papers, 180 EI papers, and has published three books as the first author. He is the recipient of Second Prize of National Technological Invention Award (2nd finisher), the Special Prize of Tianjin Technological Invention Award (1st finisher), the First Prize of Tianjin Technological Invention Award (1st finisher), and the First Prize of China Electrotechnical Society Scientific and Technological Invention Award (1st finisher).

Hong Li

School of Electrical Engineering, Beijing Jiaotong University

Title: Multi-coupling and Multi-time-scale Stability Analysis of Power Electronic Converters

Abstract:  The feedback control may cause the power electronic system to oscillate or even collapse due to its unreasonable parameters, so the stability analysis with considering the control parameters is very important. The traditional frequency-domain stability analysis method based on the small-signal modeling has limitations in the inverter stability analysis due to the existing power frequency and the complexity of the transfer functions. In this article, a time-domain stability analysis method for a grid-connected inverter with proportional-resonance (PR) control is first proposed based on Floquet theory. Meanwhile, a transfer function decomposition construction method is first proposed to obtain the time-domain model of the PR control in this article, which makes the traditional frequency-domain control be analyzed in the time domain. Furthermore, the comparison of calculation cost between the proposed stability analysis method based on the Floquet theory and the traditional frequency-domain stability analysis method is given. Finally, the simulation and experimental results prove the correctness and effectiveness of the proposed time-domain stability analysis method for the grid-connected inverter with the PR control. In this talk, a new way of stability analysis for the grid-connected inverter is provided.

Bio:  Prof. Hong LI received the B.Sc. degree from the Taiyuan University of Technology, Taiyuan, China, in 2002, the M.Sc. degree from the South China University of Technology, Guangzhou, China, in 2005, and the Ph.D. degree from the University of Hagen, Hagen, Germany, in 2009, all in electrical engineering. She is currently a Professor in Electrical Engineering at the School of Electrical Engineering, Beijing Jiaotong University, Beijing, China. She has authored or coauthored one book, 30 journal papers, and 39 conference papers. She has also applied for 20 patents. Her research interests include nonlinear modeling, analysis, and its applications, EMI suppressing methods for power electronic systems, and wide bandgap power devices and applications. Dr. Li is an Associate Editor for the IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS and the Chinese Journal of Electrical Engineering. She is a Vice Chairman of the Electromagnetic Compatibility Specialized Committee in the China Power Supply Society

Wuhua Li

College of Electrical Engineering, Zhejiang University

Title: Digital Design and Applications of High-Power Semiconductor Package

Abstract:  The digital design of power electronic device packaging is a basic technology to realize accelerated iteration of power semiconductor devices and module manufacturing. At present, packaging design mainly relies on general-purpose finite element simulation software for electronics, and the particularity of power electronic devices is not considered enough, and there are shortcomings such as weak pertinence of computing power, and low degree of digitization, and weak multi-objective optimization ability. Basic theory and platform tools for high-quality and intelligent digital design. This talk conducts a preliminary investigation of the digital design of packaging and attempts to extend the typical mechanical theories and knowledge such as partial element equivalent circuit, Fourier series heat, elastic half-space contact, etc. The comprehensive evaluation and evaluation of dynamic characteristics avoid the simple finite element numerical calculation technology, which can effectively improve the design efficiency and quality. Offer new perspectives.

Bio:  Prof. Wuhua Li received the B.Sc. and Ph.D. degrees in power electronics and electrical engineering from Zhejiang University, Hangzhou, China, in 2002 and 2008, respectively. From 2004 to 2005, he was a Research Intern, and from 2007 to 2008, a Research Assistant with the GE Global Research Center, Shanghai, China. From 2008 to 2010, he joined the College of Electrical Engineering, Zhejiang University, as a Postdoctoral. In 2010, he was promoted as Associate Professor. Since 2013, he has been a Full Professor at Zhejiang University. From 2010 to 2011, he was a Ryerson University Postdoctoral Fellow with the Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada. He has authored or co-authored more than 200 peer-reviewed technical papers and holds more than 30 issued/pending patents. His research interests include power devices, converter topologies, and advanced controls for high power energy conversion systems. Dr. Li was a recipient of the 2012 Delta Young Scholar from Delta Environmental and Educational Foundation, the 2012 Outstanding Young Scholar from the National Science Foundation of China, the 2013 Chief Youth Scientist of National 973 Program, the 2014 Young Top-Notch Scholar of National Ten Thousand Talent Program, due to his excellent teaching and research contributions, and one National Natural Science Award and four Scientific and Technological Achievement Awards from Zhejiang Provincial Government and the State Educational Ministry of China. He serves as the Associate Editor for the Journal of Emerging and Selected Topics in Power Electronics, IET Power Electronics, CSEE Journal of Power and Energy Systems, Proceedings of the Chinese Society for Electrical Engineering, a Guest Editor for IET Renewable Power Generation for Special Issue “DC and HVdc system technologies,” and a Member of Editorial Board for the Journal of Modern Power System and Clean Energy. He has been appointed as the Most Cited Chinese Researchers by Elsevier since 2014.

Teng Long

Cambridge University

Title: From Device To System, Can We Design Power Converter Without Physical Boundary?

Abstract:  Due to individually structured elements, the design of power converters remains restrictive. From semiconductors to packaging to control, a unilateral serial design approach has been the status-quo for power converter development. In quest of the revolutionary improvement of power converters, we will demonstrate a new design paradigm for power converter systems by means of structural and functional integration. Instead of the unilateral serial design process using available components, we will cohesively design the power device, packaging, and control of a power converter. Applications and working progress on integrating the control and packaging design will be given in this talk as well as new magnetic components design. This progress will lead to the final full integrated and intelligent power converter design we aim to achieve in the foreseeable future.

Bio:  Dr Teng Long is an Associate Professor of the University of Cambridge, elected Professor effective from 2022 academic year. He has established the Applied Power Electronics Laboratory (The Long Group) in the Department of Engineering and he is currently leading a research team comprised of 4 Postdoctoral Research Associates and 7 PhD students. His research portfolio covers from power electronic devices to power converters to drive and power systems, mainly for transport electrification and renewable energy applications. Since his Lectureship, Dr Long has been awarded more than GBP2.5 million research grants where half are funded by the UK government and the rest directly from industrial sponsors. Dr Long has built strong connections with industrial partners including the SAIC Motor, Dynex Semiconductor, STMicroelectronics, Siemens, CBMM, CRRC, Wuxi SES. Prior to joining Cambridge, Dr Long has worked for General Electric (GE) where he has led or played an important role in many rewarding projects such as the first transformer-less all electric oil-platform supply vessel, the first large scale all electric warship (Type 45 Destroyer), and the first electromagnetic aircraft catapult demonstrator. Dr Long has been awarded the ‘2014 GE Energy Management Engineering Award’ and two times ‘Bronze Award’ during his tenure in GE. To date, Dr Long has more than 70 academic papers published, including more than 30 journal papers. He is the inventor of 5 international patents. Dr Long received the B.Eng. from the Huazhong University of Science and Technology, China, the First Class B.Eng. (Hons.) from the University of Birmingham, UK in 2009, and the Ph.D. from the University of Cambridge, UK in 2013. Dr Long is a Chartered Engineer (CEng) registered with the UK Engineering Council.

Arokia Nathan

Darwin College, University of Cambridge

Title: Ultralow Power Flexible Electronics

Abstract:  A key design consideration in flexible electronics, particularly for wearables and sensing applications, is low voltage, low power operation. This requirement not only serves to maximise battery lifetime but crucially ensures operational stability of thin film transistor (TFT) circuits and systems. Ultralow voltage/current operation is especially important in sensor interfaces so as to achieve a high resolution of the sensory signal. This presentation will review the TFT design and materials selection strategies for ultralow power operation. We examine the main issues that lead to a high operating voltage of the TFT, and discuss processing conditions for suppressing the interface trap density. Recent advances in low-voltage thin-film transistors show it is possible for the subthreshold slope to approach the thermionic limit, q/kT. Based on these considerations, an all-inkjet-printed ultra-low-power high-gain amplifier, applied to eye movement tracking by detecting human electrooculogram signals, is presented.

Bio:  Arokia Nathan is a leading pioneer in the development and application of thin film transistor technologies to flexible electronics, display and sensor systems. Following his PhD in Electrical Engineering, University of Alberta, Canada in 1988, he joined LSI Logic USA and subsequently the Institute of Quantum Electronics, ETH Zürich, Switzerland, before joining the Electrical and Computer Engineering Department, University of Waterloo, Canada. In 2006, he joined the London Centre for Nanotechnology, University College London as the Sumitomo Chair of Nanotechnology. He moved to Cambridge University in 2011 as the Chair of Photonic Systems and Displays, and he is currently a Bye-Fellow and Tutor at Darwin College. He has over 600 publications including 4 books, and more that 150 patents and four spin-off companies. He is a Fellow of IEEE, a Distinguished Lecturer of the IEEE Electron Devices Society and Sensor Council, a Chartered Engineer (UK), Fellow of the Institution of Engineering and Technology (UK), Fellow of the Society of Information Displays (SID), and winner of the 2020 IEEE EDS JJ Ebers Award.

Xinbo Ruan

Department of Electric Engineering, Nanjing University of Aeronautics and Astronautics

Title: Second Harmonic Current Reduction Techniques for Two-Stage Single-Phase Power Converters

Abstract:  In the two-stage single-phase power factor correction ac–dc converter, the input power pulsates at twice the line frequency; while in the two-stage single-phase dc–ac inverter, the output power pulsates at twice the output frequency. Meanwhile, in the two kinds of single-phase converters, the dc port holds constant power. Consequently, the pulsating power will result in second harmonic current (SHC) in the ac–dc converter and dc–ac inverter. The SHC will propagate into the dc-dc converter, the input dc voltage source or the dc load, leading to the degradation of the conversion efficiency of the dc-dc converter, the reduction of the energy conversion efficiency of the input dc voltage source, and shortened lifetime of the input dc voltage source or the dc load. To overcome these drawbacks, it is of necessity to suppress the SHC in the dc-dc converter, the dc voltage source or the dc load. This report will firstly reveal the generating and propagating mechanism of the SHC in the two-stage single-phase converters. Then, a series of control schemes to suppress the SHC in the dc-dc converter while improving the dynamic response of the system are proposed. Besides, the electrolytic capacitor-less SHC compensator will also be presented, with which the undesired electrolytic capacitor can be removed so as to prolong the lifetime of the overall system.

Bio:  Xinbo Ruan received the B.S. and Ph.D. degrees in electrical engineering from Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, China, in 1991 and 1996, respectively. In 1996, he joined the Faculty of Electrical Engineering Teaching and Research Division, NUAA, where he became a Professor in the College of Automation Engineering in 2002 and has been engaged in teaching and research in the field of power electronics. From August to October 2007, he was a Research Fellow in the Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hong Kong, China. From March 2008 to Sep. 2011, he was also with the School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, China. He is the author or co-author of 12 books and more than 300 technical papers published in journals and conferences. His main research interests include soft-switching dc-dc converters, soft-switching inverters, power factor correction converters, modeling the converters, power electronics system integration and renewable energy generation system. Prof. Ruan was a recipient of the Delta Scholarship by the Delta Environment and Education Fund in 2003 and was a recipient of the Special Appointed Professor of the Chang Jiang Scholars Program by the Ministry of Education, China, in 2007. From 2005 to 2013, and since 2017 again, he serves as a Vice President of the China Power Supply Society. From 2014 to 2016, he served as a Vice Chair of the Technical Committee on Renewable Energy Systems within the IEEE Industrial Electronics Society. Currently, he serves as an Editor for IEEE Journal of Emerging and Selected Topics on Power Electronics and an Associate Editor for IEEE Transactions on Industrial Electronics, IEEE Transactions on Power Electronics, IEEE Open Journal of Industrial Electronics Society, and IEEE Transactions on Circuits and Systems – II: Express Briefs. He was the General Chair of IPEMC-ECCE Asia 2020 and the General Secretary of IPEMC-ECCE Asia 2009, a Technical Program Committee Chair of the IEEE 7th Annual Energy Conversion Congress and Exposition (ECCE2015), and a Tutorial Committee Chair of the IEEE 12th Annual Energy Conversion Congress and Exposition (ECCE2020). He is an IEEE Fellow.

Guobing Song

School of Electrical Engineering, Xi'an Jiaotong University

Title: Fault Coupling Characteristic and Novel Relay Protection Principle for AC/DC Hybrid Power Grids

Abstract:  The pursuit of transmission economy and control flexibility of power grid has promoted the application of power electronic devices in power system. Most of the power electronic devices in the power grid are converters, which connect AC and DC power grids. The complex coupling relation and the vulnerability constraint introduced by the converter make the traditional fault analysis theory and relay protection principle difficult to adapt in the AC/DC hybrid grid. The issue can be solved by revealing the coupling mechanism of converter stations, and taking advantage of the response characteristics and high controllability of converters. The response and transfer characteristic of converter stations at different fault stages and their analytical relations are analyzed. The fault coupling mechanism of AC/DC hybrid power grid is revealed, and the equivalent model and analysis method of converter station suitable for classification of protection principle are put forward. In order to overcome the low sensitivity problem and high-speed operation demand caused by the converters, new protection principles using converter feature are studied, including ultra-high speed protection using wavefront multidimensional information, transient protection based on frequency response characteristic of converter control system and modulating/triggering part, and active detection protection based on active injection signal of converters. On this basis, relay protection schemes suitable for AC/DC hybrid power grid are proposed. The research provides theoretical support for the safe operation of AC/DC hybrid power grid.

Bio:  Prof Guobing Song is a Professor in the School of Electrical Engineering at Xi’an Jiaotong University, China. He received his Master’s Degree in power system and automation in 2002 from Xinjiang University and his Ph.D. degree in electrical engineering in 2005 from Xi’an Jiaotong University. His research focus is on relay protection for power systems with converter-based power equipment. During Prof Song’s career, he has successfully led/completed over 50 research projects, including one National Key R&D Program of China, one Key project of the National Natural Science Foundation of China, three general programs of National Natural Science Foundation of China, and two Doctoral Scientific Fund Projects of the Ministry of Education of China. Prof Song has published over 50 SCI journal papers and over 200 EI journal papers, and holds over 50 invention patents. Prof Song is the Chairman of IEEE PES (China) AC / DC hybrid power grid protection and Control Technical Subcommittee, a committee member of Renewable Power Integration and Operation in CSEE, a committee member of Power System Control and Protection in CES, a committee member of the power electronic power system in CPSS, and a senior member of IEEE and IET. He is currently also an editorial advisory board member of Power System Protection and Control (in Chinese), Protection and Control of Modern Power Systems and other journals.

Zhou Su

Xi'an Jiaotong University

Title: Key issues towards the next generation vehicular networks

Abstract:  With the vehicular communication technologies including vehicle-to-everything (V2X), Internet of Vehicles (IoV), the efficient network connection and data exchange can be realized between vehicles and the infrastructure. However, it becomes a new challenge to provide the secure resource allocation, trustful data transmission and privacy-preserving sharing effectively. In this talk, we discuss the key issues for vehicular networks to improve the reliability, trust, and privacy.

Bio:  Zhou Su is the dean of School of Cyber Science and Engineering, Xi'an Jiaotong University. His research interests include IoT, CPS, AI security, wireless network security and optimization. He received the best paper awards of IEEE ICC2020, IEEE BigdataSE2019, IEEE GCCTC 2018, etc. He is an Associate Editor of IEEE Internet of Things Journal, IEEE Open Journal of Computer Society, etc.

Yongwen Wang

National University of Defense Technology

Title: 通用微处理器性能的再思考与再提升

Abstract:  随着领域专用处理器成为研究热点,传统的通用处理器该如何发展成为一个新的问题。本报告将回顾通用处理器性能提升的历程,研判通用处理器性能提升的空间,报告飞腾通用处理器在核心性能提升方面的工作,并探讨未来通用处理器发展的挑战和思路。

Bio:  王永文,国防科技大学计算机学院研究员,博士生导师,中国计算机学会高级会员,中国计算机学会工程与工艺专委会委员。主要研究方向是高性能微处理器体系结构及其实现技术。先后主持自然科学基金项目2项、国家科技重大专项课题2项、省部级课题5项。获全国创新争先奖牌、国家科学技术进步特等奖1项、国家科学技术进步一等奖1项、省部级科技进步一等奖4项、国家优秀专利奖1项。出版专著1部,在国内外主要刊物和学术会议上发表论文60余篇,专利授权40余项。获求是奖、政府特殊津贴。

Minghao Wen

School of Electrical and Electronic Engineering, Huazhong University of Science and Technology

Title: Relay Protection for Full Power Electronic Source based Power Grid

Abstract:  This report analyzes the problems and challenges faced by the primary and backup protection of the full power electronic source based power grid. Then, the principles of fast transient value based primary protection based on the equal transfer process of transmission lines and backup protection based on the information interconnection between electrical directly connected substations are put forward. This report preliminarily constructs the relay protection scheme of the full power electronic source based power grid and looks forward to the development direction of the new power system relay protection.

Bio:  Professor Wen Minghao is the doctoral supervisor of the School of Electrical and Electronic Engineering, Huazhong University of Science and Technology. He is the Member of National Technical Committee on Short-circuit Current Calculation of Standardization, Chairman of the Main Equipment Technical Sub-Committee of IEEE PES Protection and Control Technical Committee (China), Vice Chairman of Relay Protection and Excitation Professional Committee of China Hydropower Engineering Society. He is mainly engaged in power system relay protection, fault simulation, condition monitoring and power electronics application technology research work. From 2001 to 2003, he worked as a postdoctoral researcher in Xuji Electric Co., LTD. As the technical leader (ranked second in the appraisal), he completed the research and development of the WXH-803 microcomputer line protection device for the National Fifteen Major Technical Equipment Development Project. He has presided over a number of general projects of the National Natural Science Foundation of China and cooperative projects of enterprises. He has published more than 50 papers in important journals such as IEEE Transactions on Power Delivery and Proceedings of the CSEE. He has obtained 10 national invention patents, 1 first prize of Hubei Provincial Technical Invention, 1 first prize of Hubei Provincial Scientific and Technological Progress and 1 second prize of China Electric Power Science and Technology.

Liye Xiao

Institute of Electrical Engineering of Chinese Academy of Sciences

Title: Establishing wide-area virtual power plant based on PV-dominated energy and physical energy storage systems

Abstract:  The key issues to achieve the “dual carbon” goals mainly involve three aspects: the structure of energy and power supply, the development of energy storage technology, and the construction of new power system. Combined with the specific situation of China, this study analyzes and forecasts the power supply structure dominated by renewable energy; Considering the characteristics and development needs of renewable energy, the viewpoint and idea are put forward to develop physical energy storage, especially underground energy storage engineering, to meet the large-scale energy storage needs of power grid. On this basis, the overall idea is suggested for constructing wide area virtual power plants and future power systems.

Bio:  Professor at the Institute of Electrical Engineering, Chinese Academy of Sciences (CAS). He has successively served as Deputy Director and Director of the Institute of Electrical Engineering, CAS. He has accomplished a series of innovative achievements in advanced power technology, space-time complementarity of wide-area renewable energy, structure for the future power grid, intelligent energy network, and new power equipment technology. He has also participated in some strategic consulting and research on the energy of CAS and the Chinese Academy of Engineering. He has published about 200 academic papers. In 2002, he won the National Science Fund for Distinguished Young Scholars of the National Natural Science Foundation of China. In 2007, he won the honorary Medal of the “Ten Outstanding Young Scientist” of CAS, and in 2017, he led the team to be supported by the Creative Research Groups, National Natural Science Foundation of China. At present, Xiao Liye also acts as a Member of the International Award Committee of the Global Energy Prize, Leader of the Electrical Engineering Group of the Discipline Review Group of the State Council, and President of the Beijing Society of Electro-Technology, etc. He also serves as IEEE Transactions on Applied Superconductivity, Cryogenics, Editorial Board Member of CSEE Journal of Power and Energy System and other academic journals.

Yuedong Xu

School of Information Science and Technology, Fudan University

Title: Mercury: A Simple Transport Layer Scheduler to Accelerate Distributed DNN Training

Abstract:  Communication scheduling is crucial to accelerate the training of large deep learning models, in which the transmission order of layer-wise deep neural network (DNN) tensors is determined for a better computation-communication overlap. Prior approaches adopt user-level tensor partitioning to enhance the priority scheduling with finer granularity. However, a startup time slot inserted before every tensor partition will neutralize this scheduling gain. Tuning hyper-parameters for tensor partitioning is difficult, especially when the network bandwidth is shared or time-varying in multi-tenant clusters. In this paper, we propose Mercury, a simple transport layer scheduler that moves the priority scheduling to the transport layer at the packet granularity. The packets with the highest priority in the Mercury buffer will be transmitted first. Mercury achieves the near-optimal overlapping between communication and computation. It also leverages the immediate aggregation at the transport layer to enable the full overlapping of gradient push and pull. We implement Mercury in MXNet and conduct comprehensive experiments on five popular DNN models in various environments. Mercury can well adapt to dynamic communication and computation resources. Experimental results show that Mercury can achieve up to 2.30╳ speedup over the classical PS architecture, and 2.04╳ speedup over state-of-the-art tensor partitioning methods.

Bio:  Dr. Yuedong Xu is a Professor with School of Information Science and Technology, Fudan University, China. He received B.S. degree from Anhui University in 2001, M.S. degree from the Huazhong University of Science and Technology in 2004, and Ph.D. degree from The Chinese University of Hong Kong in 2009. From 2009 to 2012, he was a Postdoctoral Researcher with INRIA Sophia Antipolis and Université d'Avignon, France. He received the French MENRT fellowship in 2009 and the OKAWA Foundation research grant in 2019. His areas of interests include network performance evaluation, multimedia networking and distributed machine learning. He has published more than 30 papers in premier conferences and journals including ACM Mobisys, CoNEXT, Mobihoc, IEEE Infocom and IEEE/ACM ToN, IEEE JSAC.

Xu Yang

School of Electrical Engineering, Xi'an Jiaotong University

Title: Modeling and Fast Dynamic Control of Voltage Regulator for Next Generation Data Center Processors

Abstract:  With the continuous development of microprocessors, more stringent voltage regulation requirements have been put forward for the voltage regulators (VR) in the transient process. This paper proposes a driving control method for GaN devices to improve the transient response of the VR. When the GaN device conducts reverse, its source-drain voltage can be controlled by its gate voltage. During load step-down transient, the reverse conduction voltage of the GaN device is naturally applied across the inductor, which can be utilized to speed up the change rate of the inductor current. As a result, the overshoot of the output voltage can be reduced during load step-down transient. The proposed method does not need to modify the power circuit, and is easy to implement. Finally, the effectiveness of the proposed method is verified by experiments. The results show that the output voltage overshoot is reduced by 55%, and the transition time is shortened by 80% using the proposed method. The results also show that with the same overvoltage, using the proposed method can reduce the output capacitance by 57% and the transition time by 77%, thereby increasing the power density of the VR circuit and saving costs

Bio:  received the B.S. and Ph.D. degrees in electrical engineering from Xi’an Jiaotong University, Xi’an, China, in 1994 and 1999, respectively. Since 1999, he has been a Member of the Faculty of the School of Electrical Engineering, Xi’an Jiaotong University, where he is currently a Professor. From November 2004 to November 2005, he was with the Center of Power Electronics Systems, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA, as a Visiting Scholar. He then came back to Xi’an Jiaotong University, and engaged in the teaching and researches in power electronics and industrial automation area. His research interests include soft switching topologies, PWM control techniques, electromagnetic compatibility power electronic integration and packaging technologies.

Yang Yu

School of Artificial Intelligence, Nanjing University

Title: Offline Reinforcement Learning

Abstract:  to be added soon

Bio:  Yang Yu is a Professor in the School of Artificial Intelligence, Nanjing University, China. His research interest is in machine learning, mainly on reinforcement learning and derivative-free optimization for learning. His work has been published in Artificial Intelligence, IJCAI, AAAI, NIPS, KDD, etc. He has been granted several conference best paper awards including IDEAL'16, GECCO'11 (theory track), PAKDD'08, etc. He was in the Champion Team of 2018 OpenAI RetroContest, and the Grand Champion Team of PAKDD 2006 Data Mining Competition. He was recognized as one of the “AI’s 10 to Watch” by IEEE Intelligent Systems in 2018, and received the PAKDD Early Career Award in 2018. He was invited to give an Early Career Spotlight Talk in IJCAI'18. He has served as an Area Chair of AAAI'19 and IJCAI’18; a Senior PC member of IJCAI'15/17; a Publicity Co-chair of IJCAI'16/17 and IEEE ICDM'16; a Workshop Co-chair of ACML'16 and PRICAI’18.

Zhengming Zhao

Department of Electric Engineering, Tsinghua University

Title: Discrete State Event-Driven Modeling and Simulation for Power Electronic Systems

Abstract:  This presentation firstly introduces the background and challenges of modeling and simulation of power electronic systems. Then, a piecewise analytical transient (simply called PAT) model is presented, which is called time-slicing-based decoupling. Further, the Discrete State Event-Driven Modeling and Simulation for Power Electronic Systems is proposed, which is accurate and efficient simulation of power electronic systems numerical algorithm with flexible integration of continuous states. This presentation introduces the principle and characteristics of the method and exhibits the typical applications and demonstrations. The method has been developed to becoming into universal software called DSIM for power electronics simulation, which has been increasingly used in the world.

Bio:  Dr. Zhengming Zhao has obtained his bachelor and master degree from Hunan University in 1982 and 1985 respectively, and Ph.D from Tsinghua University in 1991, all in Electrical Engineering. Then he joined the faculty of Tsinghua University till now, during which he worked on postdoctoral research in USA, in the Ohio State University and University of California at Irvine in 1994-1997; and then senior visiting scholar and research professor successively in University of British Columbia and University of Hong Kong in 1998-1999. He is currently the professor of Department of Electrical Engineering in Tsinghua University. He is also the Vice Chairman of both Power Electronics Society of Chinese Electrotechnical Society and Beijing Power Electronics Society. He is IEEE Fellow and IET Fellow. Dr. Zhao also serves as Editor-in-Chief, Vice Editor-in-Chief and Associate Editor for some important International and national Journals and Transactions. His main research areas include high-power electronics technology, grid-connected photovoltaic power generation application, motor drives, and wireless power transfer.

Haibo Zhou

School of Electronic Science and Engineering, Nanjing University

Title: A Fully-Decoupled Radio Access Network Architecture for 6G

Abstract:  Currently, it is well recognized that 5G is still facing several fundamental challenges, including spectrum resource scarcity, increasing demand for high-quality network service provision, and proliferating network operation costs. Therefore, a revolutionary design of 6G with high scalability, availability and economy is required. In this talk, we introduce a disruptive fully-decoupled radio access network (FD-RAN) architecture for 6G. In the FD-RAN, base stations (BSs) are physically decoupled into control BSs and data BSs, and the data BSs are further physically split into uplink BSs and downlink BSs. With the physical split of base station functionalities, advanced cooperative transmission techniques such as coordinated multi-point (CoMP), receiver diversity, and hybrid duplex resource allocation can be naturally implemented. Our proposed FD-RAN architecture is expected to enhance the spectrum utilization, reduce the network energy consumption and improve the quality of user experience in 6G.

Bio:  Haibo Zhou is currently a Full Professor with the School of Electronic Science and Engineering, Nanjing University, Nanjing, China. He received the Ph.D. degree in information and communication engineering from Shanghai Jiao Tong University, Shanghai, China, in 2014. From 2014 to 2017, he was a Postdoctoral Fellow with the Broadband Communications Research Group, Department of Electrical and Computer Engineering, University of Waterloo. He has published 5 Books, 3 Book Chapters, and over100 high-level journal papers, including 7 ESI Highly Cited Papers. He was a recipient of 6 best journal and conference paper awards, including IEEE GLOBECOM’20, VTC’2020-Fall, and the Norbert Wiener Review Award of IEEE/CAA Journal of Automatica Sinica in 2020 etc. He was also a recipient of the IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award (2019), Chinese overseas young high-level talents (2019), and Clarivate Highly Cited Researcher (2020). He served as Track/Symposium Co-Chair for ICCC'2019, VTC-Fall'2020, VTC-Fall'2021, and Globecom’2022 ect. He is currently an Associate Editor of the IEEE TWC, IEEE IoT Journal, IEEE Network Magazine, IEEE WCL, and JCIN. His research interests include resource management and protocol design in vehicular ad hoc networks, B5G/6G networks and space-air-ground integrated networks.

Ting Zhou

Shanghai Advanced Research Institute, CAS

Title: Brain-Computer Interface: Empowering Smart Communication

Abstract:  Wireless communication has been through several generations of rapid development, and is presently stepping into the next era, which is 6G. 6G is a great blueprint where the so-called ubiquitous intelligence is believed to be realized, and that human, machine, and everything will be closely united as an inseparable whole. Therefore, brain-computer interface (BCI) is deemed a technology with great potential in supporting 6G in terms of bridging human brain and machine. Different from intrusive BCIs, whose main challenge is developing bio-friendly electrodes and chips, non-intrusive BCIs focus more on precise collection of weak electroencephalo-graph (EEG) signal, and robust encoding and decoding approaches against strong interference. For this presentation, we will discuss about non-intrusive BCIs, and more specifically about mobile and wearable EEG recording devices, efficient detection and decoding algorithms, mainstream experiment paradigms, and some specific applications of BCIs in various domains.

Bio:  Prof. Ting Zhou is now with Shanghai Advanced Research Institute, CAS. She received the B.S. and M.S. degrees from the Department of Electronic Engineering, Tsinghua University, in 2004 and 2006, respectively, and the Ph.D. degree from the Shanghai Institute of Microsystem and Information Technology (SIMIT), Chinese Academy of Sciences, in 2011. Her research interests include intelligent coordination of heterogeneous wireless networks, maritime broadband communication and BCI empowered smart communication. She has achieved outstanding technical application results in the national maritime broadband communication. She has led to win the First Prize of Shanghai Science and Technology Award in 2020 and the First Prize of Technological Invention Awards from China Institute of Communications in 2019.

Chunbo Zhu

School of Electrical Engineering, Harbin Institute of Technology

Title: State of The Arts of Dynamic Wireless Power Trarnsfer for Electric Vehicles

Abstract:  There is a continuous demand on the wireless charging for the electric vehicle (EV). Compared to the traditional wire-based charger, the user-friendly wireless power transfer (WPT) is able to offer dynamic charging even for a moving vehicle. This unique merit is particularly attractive to address the bottleneck of the EV development, i.e., limited energy density of the battery and the high frequency of the charging. As a promising charging solution, WPT has also shown great potentials in the self-driving vehicles, public transportation systems, and high-power industrial vehicles. This speech would review and compare three basic approaches for the dynamic wireless charging, and the state of the art of dynamic WPT is broadly introduced.

Bio:  Chunbo Zhu (Member, IEEE) received the B.S. and M.S. degrees in electrical engineering and the Ph.D. degree in mechanical engineering from the Harbin Institute of Technology (HIT), Harbin, China, in 1987, 1992, and 2001, respectively.,He was a Postdoctoral Research Fellow with PEI Research Center, National University of Ireland, Galway, Ireland, from 2003 to 2004. He is currently a Full Professor with HIT. He is also the Director of the Institute of Wireless Power Transfer Technology. His current research interests include energy management systems, electric and hybrid electric vehicles, and wireless power transfer technologies.

Haojin Zhu

Shanghai Jiao Tong University

Title: Security and Privacy for Artificial Intelligence of Things

Abstract:  The Artificial Intelligence of Things (AIoT) is the combination of Artificial intelligence (AI) technologies with the Internet of things (IoT), which is reshaping our daily life. However, it is also facing an increasing threat of various attacks. In this talk, we'll introduce our recent works on AIoT attacks and defense, especially related to AIoT platform security, AI voice interface security, and AI image interface security.

Bio:  Haojin Zhu (zhu-hj@cs.sjtu.edu.cn) received his B.Sc. degree (2002) from Wuhan University (China), his M.Sc.(2005) degree from Shanghai Jiao Tong University (China), both in computer science and the Ph.D. in Electrical and Computer Engineering from the University of Waterloo (Canada), in 2009. He is currently a professor with Computer Science department in Shanghai Jiao Tong University. His current research interests include IoT security and privacy enhancing technologies. He published more than 70 international journal papers, including JSAC, TDSC, TPDS, TMC, TIFS, and 90 international conference papers, including IEEE S&P, ACM CCS, USENIX Security, NDSS, ACM MOBICOM. He received a number of awards including: IEEE VTS Distinguished Lecturer (2022) ACM CCS Best Paper Runner-Ups Award (2021), IEEE TCSC Award for Excellence in Scalable Computing (Middle Career Researcher, 2020), IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award (2014), Top 100 Most Cited Chinese Papers Published in International Journals (2014), Distinguished Member of the IEEE INFOCOM Technical Program Committee (2015, 2020), best paper awards of IEEE ICC (2007) and Chinacom (2008), WASA Best Paper Runner-up Award (2017). He is serving the editorial board for IEEE Trans. on Wireless Communications and program committees for top conferences such as USENIX Security, ACM CCS, NDSS and IEEE INFOCOM.