Welcome Messages | |
Welcome to Workshop on Advances in Wireless Communications 2018 (WAWC 2018). Date: 14:00 - 17:00 Wednesday, July 18, 2018. Location: Yougu Hall, Nanjing Holiday Inn (near Mozhou East Road Subway Station ), Nanjing, China. Co-Chairs: Prof. Fu-Chun Zheng and Prof. Geoffrey Ye Li Workshop opening: 14:15-14:30, Prof. Xiaohu You | |
Keynote Speakers This line will not be displayed because COLOR: white | |
Time: 14:30 - 15:45, July 18 Speaker: Prof. Simon Godsill (University of Cambridge, UK) Title: Bayesian Learning of latent dynamic network structures and intentionality from noisy sensor data Abstract In this talk we motivate and describe methodologies for uncovering dynamic structures, linkages and intentionalities from incomplete and noisy data, potentially arriving from multiple sensors. We illustrate the methods through application to inference about destinations of shipping data, multiple object tracking data where object behaviours and linkages may be evolving over time, high frequency financial data where very noisy and incomplete information must be used to predict and react to changes in the market structure over time, and in User Interfaces for automobiles in which the task is to determine accurately and rapidly the intended icon a user is pointing at on a screen, based on the trajectory of hand motion near to the screen, and in the presence of disturbances from suspension and road surface. Biography: Prof. Simon Godsill is Professor of Statistical Signal Processing in the Engineering Department at Cambridge University. He is also a Professorial Fellow and tutor at Corpus Christi College Cambridge. He coordinates an active research group in Signal Inference and its Applications and is Head of the Signal Processing and Communications (SigProC) Laboratory at Cambridge. His group specialises in Bayesian computational methodology, multiple object tracking, audio and music processing, and financial time series modeling. A particular methodological theme over recent years has been the development of novel techniques for optimal Bayesian filtering and smoothing, using Sequential Monte Carlo or Particle Filtering methods. Prof. Godsill has published extensively in journals, books and international conference proceedings, and has given a number of high profile invited and plenary addresses at conferences such as the Valencia conference on Bayesian Statistics (twice), the IEEE Statistical Signal Processing Workshop, the Conference on Bayesian Inference for Stochastic Processes (BISP), the IEEE Workshop on Machine Learning in Signal Processing (2013) and FUSION (2016). He co-authored a Springer text Digital Audio Restoration with Prof. Peter Rayner in 1998. He was technical chair of the IEEE NSSPW workshop in 2006 on sequential and nonlinear filtering methods, and has been on the conference panel for numerous other conferences/workshops. Prof. Godsill has served as Associate Editor for IEEE Tr. Signal Processing and the journal Bayesian Analysis. He was Theme Leader in Tracking and Reasoning over Time for the UK's Data and Information Fusion Defence Technology Centre (DIF-DTC) and Principal Investigator on many grants funded by the EU, EPSRC, QinetiQ, General Dynamics, MOD, Microsoft UK, Citibank, Mastercard, Google, DSO Singapore, Huawei and Jaguar Landrover. In 2009-10 he was co-organiser of an 18 month research program in Sequential Monte Carlo Methods at the SAMSI Institute in North Carolina and in 2014 he co-organised a research programme at the Isaac Newton Institute on Sequential Monte Carlo methods. In 2018 he will be General Chair of the FUSION Conference in Cambridge. Two of his journal papers have recently received Best Paper awards from the IEEE and IET. He continues to be a Director of CEDAR Audio Ltd. (which has received numerous accolades over the years, including a technical Oscar), and for which he was a founding staff member in 1988. The company has commercialised many of the ideas from Professor Godsill's research over the years. | |
Time: 15:45- 17:00, July 18 Speaker: Prof. Sennur Ulukus (University of Maryland, USA) Title: Private Information Retrieval Abstract Private information retrieval (PIR) is a canonical problem to study the privacy of users as they download content from publicly accessible databases. In PIR, a user (retriever) wishes to download data from one or more databases in such a way that no individual database can tell which data has been retrieved. PIR has originated in the computer science literature, and has recently been revisited by the information theory community. The information-theoretic re formulation of the problem aims at determining the fundamental limits of the PIR problem, i.e., what is the largest number of bits that can be retrieved privately per bit of download, or equivalently, what is the minimum number of downloads needed per bit of private retrieval? This new information-theoretic approach also proposes novel PIR schemes which achieve or approach these fundamental limits. In this talk, I will describe the problem, summarize several break-through results in the history of this problem, and present some of the recent advances in this field. Biography: Prof. Sennur Ulukus is a Professor of Electrical and Computer Engineering at the University of Maryland at College Park, where she also holds a joint appointment with the Institute for Systems Research (ISR). Prior to joining UMD, she was a Senior Technical Staff Member at AT&T Labs-Research. She received her Ph.D. degree in Electrical and Computer Engineering from Wireless Information Network Laboratory (WINLAB), Rutgers University, and B.S. and M.S. degrees in Electrical and Electronics Engineering from Bilkent University. Her research interests are in wireless communications, information theory, signal processing, and networks, with recent focus on private information retrieval, timely status updates over networks, energy harvesting communications, information theoretic physical layer security, and wireless energy and information transfer. Dr. Ulukus is a fellow of the IEEE, and a Distinguished Scholar-Teacher of the University of Maryland. She received the 2003 IEEE Marconi Prize Paper Award in Wireless Communications, an 2005 NSF CAREER Award, the 2010-2011 ISR Outstanding Systems Engineering Faculty Award, and the 2012 ECE George Corcoran Education Award. She is a Distinguished Lecturer of the Infomation Theory Society for 2018-2019. She is on the Editorial Board of the IEEE Transactions on Green Communications and Networking since 2016. She was an Editor for the IEEE Journal on Selected Areas in Communications-Series on Green Communications and Networking (2015-2016), IEEE Transactions on Information Theory (2007-2010), and IEEE Transactions on Communications (2003-2007). She was a Guest Editor for the IEEE Journal on Selected Areas in Communications (2015 and 2008), Journal of Communications and Networks (2012), and IEEE Transactions on Information Theory (2011). She was a general TPC co-chair of 2017 IEEE ISIT, 2016 IEEE Globecom, 2014 IEEE PIMRC, and 2011 IEEE CTW. |