Prof. Jun Liu Beihang University, China | Brief Introduction: Liu Jun, Professor and Doctoral Director of School of Electronic Information Engineering, Beijing University of Aeronautics and Astronautics (BUAA), Director of Department of Communication Engineering, Responsible Professor of Sky Pro Air Land Sea Integration, National Ten Thousand People's Plan for Scientific and Technological Innovation Leadership Talent, Distinguished Professor of Beihang Lantian Scholars, has presided over over and participated in more than 20 major projects of Ministry of Science and Technology's Key Research and Development Program, key projects of the National Natural Science Foundation of China (NSF), and the Basic Strengthening of the Military Commission Science and Technology Committee. He has published nearly 100 papers in top journals/conferences such as IEEE TPDS, TMC, INFOCOM, WUWNet, etc. He has published 2 monographs, more than 20 authorized invention patents, and more than 10 software publications. His research achievements have won 4 provincial and ministerial awards. He serves as the vice-chairman of the Electronic Information Materials and Devices Expert Committee of the National Think Tank of Materials and Devices Scientists, and the co-chairman of the flagship conference on hydroacoustic networks and systems, ACM WUWNet. 汇报题目：水声携能传输与反向散射通信关键技术研究 摘要：水下信息传输作为海洋信息化发展的重要支撑技术，是近几年的研究热点之一。能耗对水下传感器节点至关重要，水下环境中能量采集并不稳定或效率低下，且水下传感器节点通常部署在难以接近的地方，给海洋信息化发展带来了困难。水声携能传输与反向散射通信技术是解决水下传感器节点能耗问题极具潜力的新技术之一，然而截至目前针对相关方向的研究还远不够深入。本次报告围绕基于压电陶瓷声电转换效应的水声携能传输与反射通信技术的最新创新性研究成果，从传能、储能到反射通信三个环节依次介绍了水声传能与数能同传波形设计，多阵元水声能量收集与能量利用管理，反射水声通信信噪比优化与抗多普勒、抗干扰等关键技术的研究内容，介绍了如何整体提升水声携能传输与反向散射通信的效率与稳健性。特别的，面对水下传感器数据采集典型应用场景，汇报包含了基于反向散射通信的感传一体传感数据纯模拟调制与相应解调方案研究，从而实现传感数据低功耗、高精度采集与传输。水声携能传输与反向散射技术的全面推进，将加快相关技术的落地应用，对于解决水下传感器能耗问题、乃至实现无源通信意义重大。 |
Prof. Tian Wang Beijing Normal University, China | Brief Introduction: Wang Tian is a Distinguished Professor of Beijing Normal University, Director of the Engineering Research Center of “Big Data, Cloud and Intelligent Collaboration” of the Ministry of Education of China, doctoral supervisor, national young top-notch talent, moderator of key R&D program of the Ministry of Science and Technology, and leader of innovation team of Guangdong ordinary universities. D. from the City University of Hong Kong, selected as one of the top 2% of global top scientists for life, and selected as one of the leading talents cultivation program of Beijing Normal University. He is engaged in research work in the field of Internet of Things and Edge Intelligence, and has published more than 50 papers in CCF Class A and IEEE/ACM Transactions series journals. His papers have been cited more than 15,000 times, with H-index of 69, 10 ESI highly cited papers (including 3 ESI hot papers), 30 authorized invention patents (1 transferred), presided over 1 National Key Research and Development Program of the Ministry of Science and Technology, 5 National Natural Science Foundation of China, and was awarded the Second Prize of Natural Science in Hunan Province, Second Prize of Scientific and Technological Advancement in Fujian Province, and Third Prize of Natural Science in Fujian Province. 汇报题目：合作式边缘智能的研究与应用 摘要：随着物联网（IoT）设备的爆炸性增长和5G网络的普及，数据量激增，对实时处理能力和低延迟的需求也日益增加。传统的云计算模型由于数据传输的延迟和带宽限制，在处理大量边缘生成的数据时面临挑战。为了解决这些问题，合作式边缘智能作为一种新兴范式，正在成为研究的热点。本报告旨在概述其关键概念、任务卸载策略、资源分配算法、技术挑战及其应用案例。 |
Assoc. Prof. Xiaolong Zheng Beijing University of Posts and Telecommunications, China | Brief Introduction: Xiaolong Zheng is an associate professor and doctoral supervisor at Beijing University of Posts and Telecommunications (BUPT), and a national young talent. He has long been engaged in research work related to intelligent IoT, presided over 2 top-level projects of National Natural Science Foundation of China (NSFC) and other important scientific research projects. He has published more than 30 academic papers in Class A journals and conferences such as IEEE/ACM TON, TMC, MobiCom, etc., and has been awarded the Best Paper Award/Best Paper Nominee Award of renowned international academic conferences for 7 times including the Best Paper Award of IEEE SECON, ACM SenSys 2023, and Best Paper Nominee Award of IEEE SECON 2022, a CCF Class B conference. 2022 Best Paper Award, ACM SenSys 2023 Best Paper Nomination Award, etc. He has been selected for the 5th China Association for Science and Technology (CAST) Young Talent Support Project, and has been awarded the ACM SIGMOBILE China Rising Star Award, the Second Prize of the Natural Science of the Chinese Computer Society, and other awards. Speech Title: AI Inference on IoT End Devices Abstract: In recent years, AI applications on IoT end devices (such as smartphones and smartwatches) have developed rapidly, with neural network-driven mobile applications becoming an indispensable part of daily life. The emergence of LLMs like ChatGPT has further elevated natural language theory and generation capabilities to new heights. However, due to the limited memory and computing resources of IoT devices, the performance of localized AI inference on the end devices is often unstable, and the fine-grained behavior during inference is difficult to measure. This talk introduces a measurement tool called nnPerf. This tool enables low-overhead measurement of kernel-level behavior during model inference on edge devices, including CPU and GPU states as well as kernel-level latency during inference. By utilizing nnPerf, it is possible to gain deep insights into fine-grained model inference on end devices, accurately identify and promptly address runtime efficiency bottlenecks, and further tackle the challenges of running complex models and improving inference efficiency on memory-and-computation-constrained end devices. |
Researcher Guibin Bian Institute of Automation Chinese Academy of Sciences, China | Brief Introduction: Guibin Bian is a researcher at the Institute of Automation, Chinese Academy of Sciences. His research interests include intelligent surgical robots. As a project leader, he is in charge of the National Key Research and Development Program, the National Key Research Instrument Development Program of the Foundation Committee, and the Innovation Cross-team Program of the Chinese Academy of Sciences. He has published more than 60 SCI papers, won 5 international conference paper awards, and 3 ESI highly cited papers. He has been authorized 40 domestic and foreign invention patents, and participated in drafting 1 national standard. He was awarded the first prize of Technical Invention Award of China Instrumentation Society as the first complete author. He is the sixth chairman of the Youth Innovation Promotion Association of the Chinese Academy of Sciences (YIPA), a member of the Expert Group of the 14th Five-Year Plan of the Ministry of Science and Technology (MOST) on “Research and Development of Basic Research Conditions and Major Scientific Instruments”, and an expert member of the Working Group on Standardization of National Public Service Robots, and has been selected as an outstanding member of YIPA, a JieYing of Beijing Municipal Government and a Beijing Science and Technology Rising Star. 汇报题目：智能显微手术机器人 摘要：显微手术机器人是精准手术和智能控制的有机结合，能够在显微外科多项术式中辅助医生实现高精准度、高灵巧性、高规范性的手术操作，是医疗手术机器人的重要分支之一。本次报告以显微眼科手术为切入点，回顾了其历史沿革和前沿成果，介绍了显微镜和手术器械在发展中的助推作用，指出新一代显微眼科手术机器人是操作自主性和灵活性更强、控制精度更高、辅助功能更加全面、术后反馈更加完善的智能手术系统。报告同时阐述了显微眼科手术机器人的几项关键技术，包括智能手术器械研发、术中实时多模态导航方法、机器人智能控制、手术智能评估等，最后展望了显微眼科手术机器人的未来机遇与挑战。 |
Asst Prof. Xiuzhen Guo Zhejiang University, China | Brief Introduction:Xiaolong Zheng is an associate professor and doctoral supervisor at Beijing University of Posts and Telecommunications (BUPT), and a national young talent. He has long been engaged in research work related to intelligent IoT, presided over 2 top-level projects of National Natural Science Foundation of China (NSFC) and other important scientific research projects. He has published more than 30 academic papers in Class A journals and conferences such as IEEE/ACM TON, TMC, MobiCom, etc., and has been awarded the Best Paper Award/Best Paper Nominee Award of renowned international academic conferences for 7 times including the Best Paper Award of IEEE SECON, ACM SenSys 2023, and Best Paper Nominee Award of IEEE SECON 2022, a CCF Class B conference. 2022 Best Paper Award, ACM SenSys 2023 Best Paper Nomination Award, etc. He has been selected for the 5th China Association for Science and Technology (CAST) Young Talent Support Project, and has been awarded the ACM SIGMOBILE China Rising Star Award, the Second Prize of the Natural Science of the Chinese Computer Society, and other awards. Speech Title:Biomagnetism for Inclusive Vital Sign Monitoring: Modeling and Implementation Abstract:Vital sign monitoring, such as tracking the heart rate (HR) and respiration rate (RR), has become a popular functionality on smart wearables. We present the design, implementation, and evaluation of MagWear, a novel biomagnetism-based system that can accurately and inclusively monitor the heart rate and respiration rate of mobile users with diverse skin tones. Firstly, we build a mathematical model that characterizes the magnetic coupling effect of blood flow under the influence of an external magnetic field. This model uncovers the variations in accuracy when monitoring vital signs among individuals. Secondly, leveraging insights derived from this mathematical model, we present a software-hardware co-design that effectively handles the impact of human diversity on the performance of vital sign monitoring, pushing this generic solution one big step closer to real adoptions. |
