Organized by Prof. Jeffrey Andrews and Prof. Hyeji Kim

Upcoming Seminars

Prof. Deniz Gündüz  
Date: Friday, October 30, 2020
Time: 9:00 AM (CDT; UTC -5)  
Access: Seminar will be delivered live 
Title: Federated Learning over wireless fading channels

Bio: Prof. Deniz Gündüz received the B.S. degree in electrical and electronics engineering from METU, Ankara, Turkey, in 2002, and the M.S. and Ph.D. degrees in electrical engineering from NYU Polytechnic School of Engineering (formerly Polytechnic University), Brooklyn, NY, in 2004 and 2007, respectively. He is currently a Reader (Associate Professor) in the Electrical and Electronic Engineering Department of Imperial College London, and is leading the Information Processing and Communications Lab. He is also the Deputy Head of the Intelligent Systems and Networks Group. Previously he was a Research Associate at CTTC, Barcelona, Spain, a Consulting Assistant Professor at the Department of Electrical Engineering, Stanford University, and a postdoctoral Research Associate at the Department of Electrical Engineering, Princeton University. He also held a visiting research collaborator position at Princeton University from October 2009 until November 2011. Dr. Gündüz is the recipient of the 2017 Early Achievement Award of the IEEE Communication Society – Communication Theory Technical Committee (CTTC), a Starting Grant of the European Research Council (ERC) in 2015, the 2014 IEEE Communication Society Best Young Researcher Award for the Europe, Middle East and Africa Region, and the 2008 Alexander Hessel Award awarded by the Electrical and Computer Engineering Department of New York University Polytechnic School of Engineering for the best Ph.D. dissertation. He is also a recipient of the Best Paper Awards at the 2016 IEEE Wireless Communications and Networking Conference (WCNC), and 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), and the Best Student Paper Award at the 2018 IEEE WCNC and 2007 International Symposium on Information Theory (ISIT).

Prof. Cong Shen  
Date: Thursday, November 5, 2020
Time: 11:00 AM (CST; UTC -6)  
Access: Seminar will be delivered live 
Title: Communication design for distributed machine learning

Bio: Cong Shen received his B.S. and M.S. degrees, in 2002 and 2004 respectively, from the Department of Electronic Engineering, Tsinghua University, China. He obtained the Ph.D. degree from the Electrical Engineering Department, University of California Los Angeles (UCLA), in 2009. Prior to joining the Electrical and Computer Engineering Department at University of Virginia, Dr. Shen was a professor in the School of Information Science and Technology at University of Science and Technology of China (USTC). He also has extensive industry experience, having worked for Qualcomm Research, SpiderCloud Wireless, Silvus Technologies, and Xsense.ai, in various full time and consulting roles. His general research interests are in the area of communication theory, wireless communications, and machine learning. He was the recipient of the “Excellent Paper Award” in the 9th International Conference on Ubiquitous and Future Networks (ICUFN 2017). Currently, he serves as an editor for the IEEE Transactions on Wireless Communications, and editor for the IEEE Wireless Communications Letters.

Prof. Jakob Hoydis  
Date: Friday, November 20, 2020
Time: 9:00 AM (CST; UTC -6)  
Access: Seminar will be delivered live 
Title: TBA

Bio: Jakob Hoydis received the diploma (Dipl.-Ing.) degree in electrical engineering and information technology from RWTH Aachen University, Germany, in 2008, and the Ph.D. degree from Supéléc, Gif-sur-Yvette, France, in 2012. He is currently the Head of the Research Department, Nokia Bell Labs, France, focusing on radio systems and artificial intelligence. Prior to this, he was a co-founder and the CTO of the social network SPRAED and worked for Alcatel-Lucent Bell Labs, Stuttgart, Germany. His research interests are in the areas of machine learning, cloud computing, SDR, large random matrix theory, information theory, signal processing, and their applications to wireless communications. He is a coauthor of the textbook Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency (2017). He was a recipient of the 2019 VTG IDE Johann-Philipp-Reis Prize, the 2019 IEEE SEE Glavieux Prize, the 2018 IEEE Marconi Prize Paper Award, the 2015 IEEE Leonard G. Abraham Prize, the IEEE WCNC 2014 Best Paper Award, the 2013 VDE ITG Förderpreis Award, and the 2012 Publication Prize of the Supéléc Foundation. He has received the 2018 Nokia AI Innovation Award, the 2018 and 2019 Nokia France Top Inventor Award, and has been nominated as an Exemplary Reviewer 2012 for the IEEE Communication Letters. He is also the Chair of the IEEE COMSOC Emerging Technology Initiative on Machine Learning as well as an Editor of IEEE Transactions on Wireless Communications.