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Dr. Youngwook Ko  BSE, MSc, PhD

Senior Lecturer in Signal Processing and Wireless Communications

Email: youngwook.ko@york.ac.uk

Tel: +44 (0)1904 322343

Research Area: Communication Technologies

Areas of Expertise: application of machine (deep) learning and signal processing for wireless communications.

Biography

Biography

Dr. Ko has a B.S.E. in Information and Communications Engineering from Hannam University, South Korea, and received his MS in 2002 and PhD in 2006, both in Electrical Engineering from Arizona State University, USA.

Since 2019, he has been working for the Department of Electronic Engineering, University of York, as a senior lecturer. Prior to this, Dr Ko worked at several places. In 2007, he joined Samsung Elec. Co., as a senior research engineer. In 2008, he returned to academia as a postdoctoral fellow in Electrical and Computer Engineering at the University of Alberta, Canada. He worked in the CCSR/5GiC, University of Surrey, UK, between 2010-2013 as a research fellow and then senior fellow. Between 2013-2019, Dr. Ko worked for the ECIT Institute at the Queen's University Belfast, as a lecturer. He has authored or co-authored over 50 publications, mainly in highly ranked IEEE international journals and at peer-reviewed IEEE flagship conferences. Dr Ko is the recipient of several EPSRC grants (e.g., EPSRC First Grant Award). He is on the Editorial Boards of the IEEE Open Journal of Vehicular Technology (OJVT) and the Elsevier Journal on Physical Communications and acts as a member of the EPSRC Peer Review Associate College. Dr Ko has actively been involved in the technical programme committee for major international conferences (e.g., PIMRC2013-present, VTC2013-present, Globecom2017). 

Publications

Publications

Publications information is available via the York Research Database

Teaching

Teaching

Dr Ko teaches on the Engineering Mathematics, Signals and Systems module.

Research

Research

Dr Ko's main research interests are the application of machine (deep) learning and signal processing for wireless communications, including the following:

  • Machine learning communication technologies for challenging environments
  • Multi-dimensional index modulation (IM)
  • AI-driven technologies for MTC autonomy
  • Drone-IoT platform for global challenges
  • Vehicular MTC
  • NOMA for the 5G-V2X