報告一👶🏼：
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.
報告二🙍🏻♂️🙆🏿♂️：
Speaker:吳俊🏏，同濟大學電子與信息工程恒达副院長❗️，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.
報告三💄：
報告人：孫富春，清華大學，教授，智能技術與系統國家重點實驗室常務副主任
題目👨🏻🏫：面向機器人靈巧操作的時空數據感知與處理
摘要: 下一代智能機器人將需要裝配視聽觸覺傳感裝置，通過多模態信息的認知傳感和動作技能學習實現更加靈巧的操作🧑🏻🦲🐍。而這些功能的實現💈，將有待於人們對視聽觸覺的表征、融合以及感知到行為映射的突破。本報告介紹了課題組研製的高分辨率四模態陣列裝置和多模態認知傳感靈巧手，傳感裝置的感知信息包含微視覺，分布式壓力覺/滑覺傳感器和溫度覺，而靈巧手則裝備了四模態傳感皮膚和擬人肌肉驅動。報告提出了較為系統的視觸覺時空數據處理方法⚽️，用於解決視覺和觸覺的聯合表征與融合👩🦳，以及感知到行為的驅動映射問題🐁。最後，一些實驗用於揭示提出的理論方法🏊🏼♂️，並指出了未來的發展方向。
簡歷💦：孫富春，清華大學計算機科學與技術系教授❤️🔥，博士生導師📵，清華大學校學術委員會委員，系學術委員會主任，智能技術與系統國家重點實驗室常務副主任。兼任國家自然基金委重大研究計劃“視聽覺信息的認知計算”指導專家組成員，中國人工智能學會認知系統與信息處理專業委員會主任，中國自動化學會認知計算與系統專業委員會主任💇♂️，國際刊物《IEEE Trans. on Fuzzy Systems》，《IEEE Trans. on Systems, Man and Cybernetics: Systems》《Mechatronics》和《International Journal of Control, Automation, and Systems (IJCAS)》副主編或領域主編♥️，國際刊物《Robotics and Autonumous Systems》和《International Journal of Social Systems》編委👩🏿💻，國內刊物《中國科學🚴🏼♀️：F輯》和《自動化學報》編委。
98年3月在清華大學計算機應用專業獲博士學位。98年1月至2000年1月在清華大學自動化系從事博士後研究🕵🏻，2000年至今在計算機科學與技術系工作。工作期間獲得的主要獎勵有：2000年全國優秀博士論文獎⚈，2001年國家863計劃十五年先進個人🎀🥨，2002年清華大學“學術新人獎”👰🏿，2003年韓國第十八屆Choon-Gang 國際學術獎一等獎第一名👨🏻🎓，2004年教育部新世紀人才獎，2006年國家傑出青年基金👯。獲獎成果6項𓀅，兩項成果獲中國人工智能學會2015年吳文俊創新獎一等獎（排名第一）和2016年吳文俊進步獎一等獎（排名第二），2014年度北京市科學技術獎（理論類）二等獎（排名第一）💁🏿♂️↩️。譯書一部，專著兩部，在國內外重要刊物發表或錄用論文200余篇，其中在IEE、IEEE匯刊🧑🏿🦲、Automatica等國際重要刊物發表論文100余篇。他領導的團隊在機器人靈巧操作和國際深度學習比賽中分別獲得第一名和第二名。此外，應邀在IEEE國際機器人與自動化會議（IEEE ICRA）、IEEE信物融合系統（IEEE CYBER）♿、IEEE 智能系統設計與應用（IEEE ISDA）🫳、IEEE 計算智能與模式識別（IEEE SoCPaR）等國際會議上做大會報告和特邀報告。
