报告一：
Speaker: Shiwen Mao, Auburn University, Auburn AL, USA
Title: On contact-free vital sign measurement in healthcare Internet of Things
Abstract: Vital signs, such as breathing and heartbeat, are useful to health monitoring since such signals provide important clues of medical conditions. Effective solutions are needed to provide contact-free, easy deployment, low-cost, and long-term vital sign monitoring. Exploiting wireless signals for contact-free vital sign monitoring will be an important part of the future healthcare Internet of Things (IoT). In this talk, we present our recent work on contact-free vital sign monitoring. The first part is to exploit channel state information (CSI) phase difference data to monitor breathing and heartbeat with commodity WiFi devices. We will present PhaseBeat, a discrete wavelet transform based design, and TensorBeat, a tensor decomposition based design, as well as our experimental study to validate their performance. The second part of this talk is to exploit a 20KHz ultrasound signal for breathing rate detection. We will present our smartphone App based implementation. Our experimental study shows that the proposed systems can achieve high accuracy under different environments for vital sign monitoring.
Biography: Shiwen Mao received his Ph.D. in electrical and computer engineering from Polytechnic University, Brooklyn, NY in 2004. He is the Samuel Ginn Distinguished Professor and Director of the Wireless Engineering Research and Education Center (WEREC) at Auburn University, Auburn, AL. His research interests include wireless networks and multimedia communications. He is a Distinguished Lecturer of the IEEE Vehicular Technology Society (VTS) for 2014-2018. He is on the Editorial Board of IEEE Transactions on Multimedia, IEEE Internet of Things Journal, IEEE Multimedia, ACM GetMobile, among others, and the Steering Committee of IEEE Transactions on Multimedia and IEEE Transactions on Network Science and Engineering. He is a TPC/Symposium Co-Chair of IEEE INFOCOM 2018, IEEE ICC 2017, IEEE WCNC 2017, among others. He received the 2015 IEEE ComSoc TC-CSR Distinguished Service Award, the 2013 IEEE ComSoc MMTC Outstanding Leadership Award, and the NSF CAREER Award in 2010. He is a co-recipient of the Best Demo Award from IEEE SECON 2017, the Best Paper Awards from IEEE GLOBECOM 2016 & 2015, IEEE WCNC 2015, and IEEE ICC 2013, and the 2004 IEEE Communications Society Leonard G. Abraham Prize in the Field of Communications Systems.
报告二：
Speaker:吴俊，同济大学电子与信息工程学院副院长，教授
Title：Wireless image/video transmission with support of big data
Abstract: The tradition radio access network is built on the specific hardware platform, now is evolving towards cloud computing platform. With the new cloud radio access network (C-RAN) architecture, the communication and computation is converging, which facilitates the Base Station (BS) to utilize big data to assist data communication. The image communication is very popular with wide use of cloud storage and wechat, which produces big data traffics. The emergence of visual big data is a double edged sword to mobile communications. It puts forward a huge challenge to the wireless networks, while its abundant information provides potential to improve the spectrum efficiency significantly. We propose a novel data assisted communication of mobile image (DAC-Mobi) scheme, which utilizes a large amount of correlated (similar) images stored in the cloud to improve the spectrum efficiency and visual quality. The Simulations show that the proposed scheme outperforms conventional digital schemes about 4 dB in peak signal to noise power ratio (PSNR) and achieves 2 dB gain over the state-of-the-art uncoded transmission. At low signal to noise power ratio (SNR), an additional 2-3dB gain is achieved.
Biography: Jun Wu received his B.S. degree and M.S in Information Engineering from XIDIAN University in 1993 and 1996, respectively. He received his Ph.D. degrees in Information Engineering from Beijing University of Posts and Telecomm. in 1999. Wu joined Tongji University as a Professor in Dec. 2010. He has been a principal scientist in Huawei from 2009 to 2010, and also a principal scientist in Broadcom Inc. from 2006 to 2009. His research interests include information theory, wireless communication, and digital signal processing. He has authored or co-authored over 100 papers, two chapters of a book, and filed 23 patents (8 patents are granted in USA).
Wu is currently an IEEE senior member, ACM member, senior member of Chinese Institute of Electronics (CIE). He is serving as an Associate Editor of IEEE Transactions on Multimedia (TMM), Associate Editor of IEEE Wireless Communications Letters (WCL) and editor of Wireless Communication and Mobile Computing (WCMC). He served as IEEE GlobeCom 2016 Symposium Chair of Communications Software, Services and Multimedia Apps, Chinacom 2015 TPC Co-chair, IEEE ICCC 2014 Wireless Networking and Multimedia Symposium Co-chair.
报告三：
报告人：孙富春，清华大学，教授，智能技术与系统国家重点实验室常务副主任
题目：面向机器人灵巧操作的时空数据感知与处理
摘要: 下一代智能机器人将需要装配视听触觉传感装置，通过多模态信息的认知传感和动作技能学习实现更加灵巧的操作。而这些功能的实现，将有待于人们对视听触觉的表征、融合以及感知到行为映射的突破。本报告介绍了课题组研制的高分辨率四模态阵列装置和多模态认知传感灵巧手，传感装置的感知信息包含微视觉，分布式压力觉/滑觉传感器和温度觉，而灵巧手则装备了四模态传感皮肤和拟人肌肉驱动。报告提出了较为系统的视触觉时空数据处理方法，用于解决视觉和触觉的联合表征与融合，以及感知到行为的驱动映射问题。最后，一些实验用于揭示提出的理论方法，并指出了未来的发展方向。
简历：孙富春，清华大学计算机科学与技术系教授，博士生导师，清华大学校学术委员会委员，系学术委员会主任，智能技术与系统国家重点实验室常务副主任。兼任国家自然基金委重大研究计划“视听觉信息的认知计算”指导专家组成员，中国人工智能学会认知系统与信息处理专业委员会主任，中国自动化学会认知计算与系统专业委员会主任，国际刊物《IEEE Trans. on Fuzzy Systems》，《IEEE Trans. on Systems, Man and Cybernetics: Systems》《Mechatronics》和《International Journal of Control, Automation, and Systems (IJCAS)》副主编或领域主编，国际刊物《Robotics and Autonumous Systems》和《International Journal of Social Systems》编委，国内刊物《中国科学：F辑》和《自动化学报》编委。
98年3月在清华大学计算机应用专业获博士学位。98年1月至2000年1月在清华大学自动化系从事博士后研究，2000年至今在计算机科学与技术系工作。工作期间获得的主要奖励有：2000年全国优秀博士论文奖，2001年国家863计划十五年先进个人，2002年清华大学“学术新人奖”，2003年韩国第十八届Choon-Gang 国际学术奖一等奖第一名，2004年教育部新世纪人才奖，2006年国家杰出青年基金。获奖成果6项，两项成果获中国人工智能学会2015年吴文俊创新奖一等奖（排名第一）和2016年吴文俊进步奖一等奖（排名第二），2014年度北京市科学技术奖（理论类）二等奖（排名第一）。译书一部，专著两部，在国内外重要刊物发表或录用论文200余篇，其中在IEE、IEEE汇刊、Automatica等国际重要刊物发表论文100余篇。他领导的团队在机器人灵巧操作和国际深度学习比赛中分别获得第一名和第二名。此外，应邀在IEEE国际机器人与自动化会议（IEEE ICRA）、IEEE信物融合系统（IEEE CYBER）、IEEE 智能系统设计与应用（IEEE ISDA）、IEEE 计算智能与模式识别（IEEE SoCPaR）等国际会议上做大会报告和特邀报告。
