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关于开展休斯敦大学Zhu Han教授线上系列学术讲座的通知

发布日期 :2021-05-26作者 :点击 :


讲座一MetaSensing: Reconfigurable intelligent surface Assisted RF 3D Sensing using Machine Learning



Reconfigurable intelligent surface (RIS) stands out as a novel approach to improve the communication and sensing in the future wireless networks. It is capable to actively shape the uncontrollable wireless environments into a desirable form via flexible phase shift reconfiguration without extra hardware or power costs. To better exploit the potential of such a technique, it is essential to develop distributed configuration, to design new protocols, to explore and implement suitable application scenarios, as well as to perform intelligent control and orchestration. First we provide a general introduction of the intelligent meta-surface along with the state-of-the-art research in different areas. Then we introduce the unique features of intelligent meta-surface which enlighten its broad applications to communication and sensing, in a comprehensive way. Related design, analysis, optimization, and signal processing techniques will be presented. Finally, we explore typical meta-surface applications and discuss implementation issues with an emphasis on high-resolution smart RF sensing. Formalized analysis of several up-to-date challenges and technical details on system design will be provided for different applications.


会议ID609 475 341


讲座二Secure Computation with Privacy Preservation for Cyber Physical System Applications



Cyber Physical System (CPS) have infiltrated into many areas such as aerospace, automobiles, chemical processing, civil infrastructure, energy, healthcare, transportation, entertainment, and consumer appliances due to their tight integration of computation and networking capabilities to  monitor and control the underlying systems. Many domains of CPS such as smart metering, sensor/data aggregation, crowd sensing, traffic control etc., typically collect huge amounts of individual information for data analysis and decision making, therefore privacy is a serious concern in CPS. Most of the traditional approaches protect the privacy of individual’s data by employing trusted third parties or entities for data collection and computation. An important challenge in these large-scale distributed applications is how to protect the privacy of the participants during computation and decision making, especially when such third party entities are untrusted. Considering various CPS applications involving modeling, we first discuss on utilizing applied cryptographic techniques for privacy preserving secure computation. Then we focus on the differential privacy based secure computation that guarantees individual privacy in presence of untrusted third party entities. Since confidential information must not be inappropriately released, and the use of untrusted information must not corrupt trusted computation and the utility. This talk concludes by focusing on the development of such tools for state-of-the-art applications by considering application-specific information security requirements.


会议ID362 498 052


讲座三:Mean Field Game Tutorial and Examples



Mean field games (MFGs) deal with the study and analysis of differential games (DGs) with a large number of indistinguishable, rational, and heterogeneous players. These methodologies approximate the Nash equilibriums for DGs with symmetric interactions among players. In contrast with classical game theory, MFGs model the interaction of a representative player with the collective behavior of the other players. In this talk, we discuss the basic concepts behind MFGs as well as their difference with classical game theory techniques. Moreover, we introduce analytic and probabilistic methods that solve for the Nash equilibrium of a MFG. Finally, we conclude with the many recent applications of MFGs in engineering such as future 5G networks, ultra dense networks, UAV networks, social networks, smart grid and security.


会议ID202 550 666


二、主讲人:Prof.Zhu Han

Zhu Han received the B.S. degree in electronic engineering from Tsinghua University, in 1997, and the M.S. and Ph.D. degrees in electrical engineering from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2002, he was an R&D Engineer of JDSU, Germantown, Maryland. From 2003 to 2006, he was a Research Associate at the University of Maryland. From 2006 to 2008, he was an assistant professor in Boise State University, Idaho. Currently, he is a John and Rebecca Moores Professor in Electrical and Computer Engineering Department as well as Computer Science Department at University of Houston, Texas. His research interests include security, wireless resource allocation and management, wireless communication and networking, game theory, and wireless multimedia. Dr. Han is an NSF CAREER award recipient 2010. Dr. Han has several IEEE conference best paper awards, and winner of 2011 IEEE Fred W. Ellersick Prize, 2015 EURASIP Best Paper Award for the Journal on Advances in Signal Processing and 2016 IEEE Leonard G. Abraham Prize in the field of Communication Systems (Best Paper Award for IEEE Journal on Selected Areas on Communications). Dr. Han is the winner 2021 IEEE Kiyo Tomiyasu Award. He has been IEEE fellow since 2014, AAAS fellow since 2020 and IEEE Distinguished Lecturer from 2015 to 2018. Dr. Han is 1% highly cited researcher according to Web of Science since 2017.






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