Neural MIMO Detection: Recent Results and Future Directions
Nokia Bell Labs, Paris, France
- Jakob Hoydis
Jakob Hoydis received the diploma degree (Dipl.-Ing.) in electrical engineering and information technology from RWTH Aachen University, Germany, and the Ph.D. degree from Supelec, Gif-sur-Yvette, France, in 2008 and 2012, respectively. He is a member of technical staff at Nokia Bell Labs, France, where he is investigating applications of deep learning for the physical layer. Previous to this position he was co-founder and CTO of the social network SPRAED and worked for Alcatel-Lucent Bell Labs in 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 co-author of the textbook "Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency" (2017). He is recipient of the 2018 Marconi Prize Paper Award, the 2015 Leonard G. Abraham Prize, the IEEE WCNC 2014 best paper award, the 2013 VDE ITG Forderpreis, and the 2012 Publication Prize of the Supélec Foundation. He has received the 2018 Nokia AI Innovation Award and has been nominated as an Exemplary Reviewer 2012 for the IEEE Communication Letters. He is currently chair of the IEEE COMSOC Emerging Technology Initiative on Machine Learning for Communications as well as editor for IEEE Transactions on Wireless Communications.