Prof. Tianyou Chai
Northeastern University, China
Academician of the Chinese Academy of Engineering, IEEE Fellow, IFAC Fellow
Speech Title: Development Directions of Industrial Intelligence
Abstract: In this talk, the role of industrial automation and information technology in the industrial revolutions is analyzed, as well as the current status and main problems in automation and information for manufacturing enterprise. The connotation of industrial intelligence and the challenges in realizing industrial intelligence are put forward. Based on the analysis and application cases of industrial internet and industrial artificial intelligence, the technical basis of industrial intelligence is presented. Then, the research directions, ideas and methods of industrial intelligence are proposed.
Bio: Chai Tianyou received the Ph.D. degree in control theory and engineering from Northeastern University, Shenyang, China, in 1985.
He has been with the Research Center of Automation, Northeastern University since 1985, where he became a Professor in 1988 and a Chair Professor in 2004. He is the founder and Director of the Research Center of Automation, which became a National Engineering and Technology Research Center in 1997 and The State Key Laboratory of Synthetical Automation for Process Industries in 2011. He has made a number of important contributions in control technologies and applications. He has published two monographs，130 peer reviewed international journal papers and around 224 international conference papers. He has been invited to deliver more than 30 plenary speeches in international conferences of IFAC and IEEE. His current research interests include adaptive control, intelligent decoupling control, integrated plant control and system, and the development of control technologies with applications to various industrial processes.
Prof. Chai is a member of Chinese Academy of Engineering, an academician of International Eurasian Academy of Sciences, IEEE Fellow and IFAC Fellow. He is a distinguished visiting fellow of The Royal Academy of Engineering (UK) and an invitation fellow of Japan Society for the Promotion of Science (JSPS). For his contributions, he has won three prestigious awards of National Science and Technology Progress, the 2002 Technological Science Progress Award from Ho Leung Ho Lee Foundation, the 2007 Industry Award for Excellence in Transitional Control Research from IEEE Control Systems Society and the 2010 Yang Jia-Chi Science and Technology Award from Chinese Association of Automation.
柴天佑教授，中国工程院院士。1947 年11 月生，博士，教授，国际欧亚科学院院士，IEEE Fellow，IFAC Fellow。现任流程工业综合自动化国家重点实验室主任、东北大学国家冶金自动化工程技术研究中心主任。担任国家自然科学基金委员会信息科学部主任、东北大学第六届学术委员会主任、国家“863计划“先进制造与自动化领域专家委员会副主任、国家重点基础研究发展计划（973计划）项目首席科学家、教育部创新团队和国家自然科学基金委创新群体负责人。曾获国家科技进步二等奖三项，省部级特等奖、一等奖十项；获何梁何利科学技术进步奖，全国“五一劳动奖章”。2007年获IEEE系统与控制大会（MSC）颁发的控制研究杰出工业成就奖。发表的论文被SCI检索收录84篇，被EI检索收录322篇，被ISTP检索收录159篇，著作2部。主要研究方向：自适应控制、智能解耦、流程工业综合自动化等。
Prof. Ke Wu
University of Montreal, Canada
Academician of the Canadian Academy of Engineering (CAE), IEEE Fellow
Speech Title: Towards Batteryless IoT Networking and Sensing: Radiative Wireless Power Transfer and Harmonic Backscattering
Abstract: One essential foundation of IoT technology is the development of numerous interrelated IoT sensing and communicating nodes distributed extensively in our environment. Conventional batteries/cords-based powering solutions are certainly not an acceptable long-term and sustainable solution, considering the incurred cost, feasibility, and most of all, environmental impact. A promising and “green” powering alternative solution for IoT networking and sensing devices is recycling omnipresent ambient RF energy. The concept of harnessing wireless energy for powering IoT systems requiring a higher power supply is also feasible through dedicated wireless power base-stations, which can be an effective supplement. To realize RF power scavenging and recycling, this talk focuses on two mainstream techniques: radiative or far-field wireless power transfer (WPT) and harmonic backscattering. As an exploratory study, a survey of ambient RF energy density in the core areas of Montreal is presented first. Then, design and optimization techniques regarding low-power far-field rectifiers and fully passive harmonic transponders are presented.
Bio: Professor of electrical engineering at École Polytechnique (University of Montreal), Dr. Ke Wu is Industrial Research Chair in Future Wireless Technologies and the Director of the Poly-Grames Research Center. He was the Canada Research Chair in RF and millimeter-wave engineering and the Founding Director of the Center for Radiofrequency Electronics Research of Quebec. He has authored/co-authored over 1400 referred papers, and a number of books and book chapters and filed more than 80 patents. Dr. Wu was the general chair of the 2012 IEEE MTT-S International Microwave Symposium, and the 2016 President of the IEEE Microwave Theory and Techniques Society (MTT-S). He also served as the inaugural North American representative in the General Assembly of the European Microwave Association. He was the recipient of many awards and prizes. He was an IEEE MTT-S Distinguished Microwave Lecturer. Dr. Ke Wu is a Fellow of the IEEE, the Canadian Academy of Engineering, the Royal Society of Canada (Academy of Science), and the German National Academy of Science and Engineering.
吴柯是法国格勒诺布尔大学国家工程学院博士，加拿大皇家科学院和工程院两院院士，国际电子和电气工程协会(IEEE) 会士(FELLOW)，加拿大蒙特利尔大学工学院电气工程系终身教授，加拿大国家射频和微波重点实验室主任和世界著名的Poly-Grames 研究中心创始人，中国国家重点毫米波实验室学术委员会主任。IEEE国际会议的组织委员或顾问委员及分组主席，是IEEE-Trans.MTT、IEEE-Tans.AP、IEEE- MGWL等许多期刊的编委。
Prof. David J. Moss
Swinburne University of Technology, Australia
Fellow of the IEEE Photonics Society, Optical Society of America, and the SPIE
Speech Title: Ultra-high Bandwidth Applications of Integrated Kerr Optical Frequency Microcombs
Abstract: This talk will focus on our work on ultrahigh bandwidth applications of Kerr microcombs to optical neural networks, optical data transmission and microwave photonics. Convolutional neural networks (CNNs) are a powerful category of artificial neural networks that can extract the hierarchical features of raw data to greatly reduce the network complexity and enhance the accuracy for machine learning tasks such as computer vision, speech recognition, playing board games and medical diagnosis. Optical neural networks can dramatically accelerate the computing speed to overcome the inherent bandwidth bottleneck of electronics. We use a new and powerful class of micro-comb called soliton crystals that exhibit robust operation and stable generation as well as a high intrinsic efficiency with an extremely low spacing of 48.9 GHz. We demonstrate a universal optical vector convolutional accelerator operating at 11 Tera-OPS/s (TOPS) on 250,000 pixel images. We use the same hardware to form a deep optical CNN, achieving successful recognition of full 10 digits. We also report world record high data transmission over standard optical fiber from a single optical source, at 44.2 Terabits/s over the C-band. We achieve error free transmission across 75 km of standard optical fiber in the lab and over a field trial with a metropolitan optical fiber network. Our work demonstrates the ability of optical soliton crystal micro-combs to exceed other approaches in performance for the most demanding practical optical communications applications.
Bio: David J. Moss (S’83–M’88–SM’09–F’16) received the B.Sc. degree in physics from the University of Waterloo, Waterloo, ON, Canada, and the M.Sc. and Ph.D. degrees in nonlinear optics from the University of Toronto, Toronto, ON, in 1983 and 1988, respectively. He is the Director of the Optical Science Centre with the Swinburne University of Technology, Melbourne, Australia, leading research programs in integrated nonlinear nanophotonics, microwave photonics, telecommunications, quantum optics, biophotonics, renewable energy, and other areas. He has about 600 journal/conference papers including two Nature, a Science, eight Nature Photonics, and five Nature Communications papers. Dr. Moss received the 2011 Australian Museum Eureka Science Prize and the Google Australia Award for innovation in computer science. He has been active on many conference committees, including the General Program Chair of OSA Integrated Photonics Research in Vancouver, July 2016, and the General Chair in New Orleans, 2017. He is a Fellow of the IEEE Photonics Society, the Fellow of the Optical Society of America, and the SPIE.
Prof. Guifang Li
The University of Central Florida, USA
IEEE, OSA, SPIE Fellow
Speech Title: Few-Mode Photonic Systems
Abstract: Optical devices and systems such as lasers and fiber-optic communication systems have traditionally operated in single mode. Recently, spatial modes have been recognized as an underutilized resource that can improve system performance. This talk will present recent research in few-mode photonic systems for applications in optical fiber communication, free-space optical communication, secure communication, microwave photonics and LiDAR.
Bio: Guifang Li received his Ph.D. degree from The University of Wisconsin at Madison and is Professor of Optics and ECE at The University of Central Florida. He is the recipient of the NSF CAREER award and the Office of Naval Research Young Investigator award. Dr. Li is a Fellow of IEEE, the Optical Society (OSA), SPIE and the National Academy of Inventors. He currently serves as Editor-in-Chief of Optica’s Advances in Optics and Photonics.