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TU Berlin

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Prof. Dr.-Ing. Slawomir Stanczak

Lupe

Slawomir Stanczak studied electrical engineering with specialization in control theory at the Wroclaw University of Technology and at the Technical University of Berlin (TU Berlin). He received the Dipl.-Ing. degree in 1998 and the Dr.-Ing. degree (summa cum laude) in electrical engineering in 2003, both from TU Berlin; the Habilitation degree (venialegendi) followed in 2006. Since 2015, he has been a Full Professor for network information theory with TU Berlin and the head of the Wireless Communications and Networks department at Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (HHI). Prof. Stanczak has been involved in research and development activities in wireless communications since 1997. In 2004 and 2007, he was a Visiting Professor with RWTH Aachen University and in 2008, he was a Visiting Scientist with Stanford University, Stanford, CA, USA. He is a co-author of two books and more than 200 peer-reviewed journal articles and conference papers in the area of information theory, wireless communications, signal processing and machine learning. Prof. Stanczak received research fellowships from the German Research Foundation and the Best Paper Award from the German Communication Engineering Society in 2014. He was a Co-chair of the 14th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2013). Between 2009 and 2011, he was an Associate Editor of the European Transactions for Telecommunications (information theory) and an Associate Editor of the IEEE Transactions on Signal Processing between 2012 - 2015 and the chair of the ITU-T Focus Group on Machine Learning for Future Networks including 5G from 2017 - 2020. Since 2020, Prof. Stanczak is chairman of the 5G BERLIN association and since 2021 he is coordinator of the 6G-RIC (Research & Innovation Cluster).    

Teaching

    • Summer 2022

      • VL Theory and Algorithms of Machine Learning (Prof. Dr.-Ing. Slawomir Stanczak)
      • VL Modern Signal Processing and Communications (Dr. Renato L.G. Cavalcante)
      • VL Selected Topics in Wireless Communications and Networking (Dr. Zoran Utkovski)
      • Master Project Network Information Systems (Dr.- Ing. Julius Schulz- Zander)

    • Winter 2021/22

      • VL Fundamentals of Digital Wireless Communication (Prof. Dr.-Ing. Slawomir Stanczak)
      • VL Mathematical Introduction to Machine Learning (Dr. rer. nat. Igor Bjelakovic)

    • Summer 2021

      • VL Theory and Algorithms of Machine Learning (Prof. Dr.-Ing. Slawomir Stanczak)
      • VL Modern Signal Processing and Communications (Dr. Renato L.G. Cavalcante)
      • VL Selected Topics in Wireless Communications and Networking (Dr. Zoran Utkovski)
      • Master Project Network Information Systems (Dr.- Ing. Julius Schulz- Zander)

    • Winter 2020/21

      • VL Fundamentals of Digital Wireless Communication (Prof. Dr.-Ing. Slawomir Stanczak)
      • VL Mathematical Introduction to Machine Learning (Dr. rer. nat. Igor Bjelakovic)
      • VL Introduction to Game Theory with Engineering Applications (Prof. Dr.-Ing. Setareh Maghsudi)

    • Summer 2020

      • VL Theory and Algorithms of Machine Learning (Prof. Dr.-Ing. Slawomir Stanczak)
      • VL Modern Signal Processing and Communications (Dr. Renato L.G. Cavalcante)
      • VL Selected Topics in Wireless Communications and Networking (Dr. Zoran Utkovski)

    • Winter 2019/20

      • VL Fundamentals of Digital Wireless Communication (Prof. Dr.-Ing. Slawomir Stanczak)
      • VL Mathematical Introduction to Machine Learning (Dr. rer. nat. Igor Bjelakovic)

    •  Summer 2019

      • VL Theory and Algorithms of Machine Learning (Prof. Dr.-Ing. Slawomir Stanczak)
      • VL Modern Signal Processing and Communications (Dr. Renato L.G. Cavalcante)
      • VL Selected Topics in Wireless Communications and Networking (Dr. Zoran Utkovski)

     

    You can also find me on:

    Fraunhofer Heinrich-Hertz-Institut

    Google Scholar

    arXiv

    LinkedIn


    Publications

    Preprints

    J. Schreck and P. Jung and S. Stanczak (2015). Compressive Rate Estimation with Applications to Device-to-Device Communications. Preprint (available at http://arxiv.org/abs/1504.07365)



    H. Boche and S. Stanczak (2005). Some Comments on the Perron Root of Irreducible Matrices. Preprint



    Books

    Book Chapters

    Journal Publications

    R. Hernangómez and A. Santra and S. Stanczak (2020). A Study on Feature Processing Schemes for Deep-Learning-Based Human Activity Classification Using Frequency-Modulated Continuous-Wave Radar. IET Radar, Sonar & Navigation, Volume 14, Issue 7, July 2020, 10 pp.


    C.- X. Wang, M. Di Renzo, S. Stanczak, S. Wang and E. G. Larsson (2020). Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges. IEEE Wireless Communications (Volume 27, Issue: 1, pp. 16-23, Feb.


    G. Bräutigam, R. L.G. Cavalcante, M. Kasparick, A. Keller and S. Stanczak (2020). AI and open interfaces: Key enablers for campus networks. ITU News Magazine - AI and Machine Learning in 5G, no. 5, p. 55, open access, Dec.


    R.L.G. Cavalcante and Q. Liao and S. Stanczak (2019). Connections between spectral properties of asymptotic mappings and solutions to wireless network problems. IEEE Transactions on Signal Processing, Feb. 2019


    S. Limmer and S. Stanczak (2018). A Neural Architecture for Bayesian Compressive Sensing over the Simplex via Laplace Techniques. IEEE Trans. on Signal Processing, 66(22):6002-6015, Nov. 2018.


    C. Bockelmann and N. Pratas and G. Wunder and S. Saur and M. Navorro and D. Gregoratti and G. Vivier and E. de Carvalho and Y. Ji and C. Stefanovic and P. Popovski and Q. Wang and M. Schellmann and E. Kosmatos and P. Demestichas and M. Raceala-Motoc and P. Jung and S. Stanczak and A. Dekorsy (2018). Towards Massive Connectivity Support for Scalable mMTC Communications in 5G networks. IEEE Access (Volume: 6), pages 28969 - 28992, May 16, 2018


    J. Schreck and P. Jung and S. Stanczak (2018). Compressive Rate Estimation with Applications to Device-to-Device Communications. IEEE Transactions on Wireless Communications


    W. Samek, S. Stanczak and T. Wiegand (2017). The Convergence of Machine Learning and Communications. ITU Journal: ICT Discoveries, Special Issue No. 1


    R.L.G. Cavalcante, M. Kasparick and S. Stanczak (2017). Max-Min Utility Optimization in Load Coupled Interference Networks. IEEE Transactions on Wireless Communications, vol. 16, no. 2, pp. 705-716, Feb. 2017


    J. Mohammadi and S. Limmer and S. Stanczak (2016). A Decentralized Eigenvalue Computation Method for Spectrum Sensing Based on Average Consensus. Frequenz, July 2016


    Conference, Symposium, and Workshop Papers

    Manjunath, Ramya Panthangi and Schubert, Martin and Cavalcante, RL G and Boban, Mate and Zhou, Chan and Stanczak, Slawomir (2021). Proactive Application Rate Requirement Adaptation Mechanism for Sidelinks. 2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 1–6.


    Dai, Sida and Kurras, Martin and Thiele, Lars and Stanczak, Slawomir and Chen, Litao and Zhong, Zhimeng (2021). Deep Learning for Massive MIMO: Channel Completion for TDD Downlink. 2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 696–702.


    Bezmenov, Maria and Utkovski, Zoran and Sambale, Klaus and Stanczak, Slawomir (2021). Semi-Persistent Scheduling with Single Shot Transmissions for Aperiodic Traffic. 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), 1–7.


    O. Taghizadeh and S. Stanczak and H. Iimori and G. T. Freitas de Abreu (2020). Full-Duplex AF MIMO Relaying: Impairments Aware Design and Performance Analysis. 2020 IEEE Global Communications Conference: Signal Processing for Communications (Globecom2020 SPC), December 7 - 11, in Taipei, Taiwan


    A. Pfadler and P. Jung and S. Stanczak (2020). Mobility Modes for Pulse-Shaped OTFS with Linear Equalizer. IEEE Globecom 2020, December 7-11, Taipei, Taiwan


    P. Agostini and Z. Utkovski and S. Stanczak (2020). Channel Charting: an Euclidean Distance Matrix Completion Perspective. ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 4-8 May 2020 in Barcelona, Spain


    D.F. Külzer and S. Stanczak and M. Botsov (2020). Novel QoS Control Framework for Automotive Safety-Related and Infotainment Services. IEEE Wireless Communications and Networking Conference 2020, May 25-28, Virtual Conference


    A. Pfadler and P. Jung and S. Stanczak (2020). Pulse-Shaped OTFS for V2X Short-Frame Communication with Tuned One-Tap Equalization. 24th International ITG Workshop on Smart Antennas, Poster presentation, February 18-20, 2020 in Hamburg, Germany


    M. Mehlhose and D. A. Awan and R. L.G. Cavalcante and M. Kurras and S. Stanczak (2020). Machine Learning-Based Adaptive Receive Filtering: Proof-of-Concept on an SDR Platform. accepted, IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020


    J. Fink and M. Kasparick and S. Stanczak (2020). Robust Submodular RRH Selection for Joint Multicast Downlink Transmission. 24th International ITG Workshop on Smart Antennas (WSA 2020), Hamburg, Germany, 18-20 Feb. 2020


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    Head of Chair

    Prof. Dr.-Ing. Slawomir Stanczak
    HFT 400a
    Einsteinufer 25
    10587 Berlin
    Tel.: +49(0)30 314-28465
    Fax: +49(0)30 314-28320

    Website

    Chairman of ITU-T Focus Group on Machine Learning for Future Networks including 5G

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