Jakob Hoydis is a member of technical staff at Nokia Bell Labs, France, where he is investigating since several years applications of deep learning for the physical layer. Before this position he was co-founder and CTO of the social network SPRAED and worked for Alcatel-Lucent Bell Labs in Stuttgart, Germany. He received the diploma degree (Dipl.-Ing.) in electrical engineering and information technology from RWTH Aachen University, Germany, and the Ph.D. degree from Supélec, Gif-sur-Yvette, France, in 2008 and 2012, respectively. 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 recipient of the 2012 Publication Prize of the Supélec Foundation, the 2013 VDE ITG Förderpreis, the 2015 Leonard G. Abraham Prize, as well as the Marconi Prize of the IEEE COMSOC. He received the WCNC’2014 best paper award and has been nominated as an Exemplary Reviewer 2012 for the IEEE Communication letters. He has co-authored the textbook Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency in 2017.