Rakovic Valentin

Valentin Rakovic is an Associate Professor at the Faculty of Electrical Engineering and Information Technologies, Ss Cyril and Methodius University in Skopje. He is the head of the Laboratory for Wireless and Mobile Networks. During 2019, he worked as a visiting Research Faculty in the College of Computing at Georgia Institute of Technology, GA, USA. He has been part of multiple national and regional projects, as well as  10+ internationally funded research projects funded by the European Union and NATO. He has coauthored more than 80 publications in established international conferences and journals. His current research interests include wireless networks, signal processing, optimization theory, machine learning, and prototyping of wireless networking solutions. His most recent research activities and interests focus on the synergy between wireless communications and distributed learning, application of Federated Learning in IoT, as well as statistical learning theory for distributed and high-dimensional systems.

He is the youngest recipient of the Ss Cyril and Methodius award and is also the recipient of several international awards, most notably the IEEE DySPAN best demo award in 2011 and 2015.



PhD – Ss Cyril and Methodius University in Skopje (Joint supervision with RWTH Aachen, Germany), 2016

MSc. – Ss Cyril and Methodius University in Skopje, 2010

BSc. – Ss Cyril and Methodius University in Skopje, 2008


Publications (most recent)

  1. M. Poposka, S. Pejoski, V. Rakovic, D. Denkovski, H. Gjoreski and Z. Hadzi-Velkov, “Delay Minimization of Federated Learning Over Wireless Powered Communication Networks,” in IEEE Communications Letters, doi: 10.1109/LCOMM.2023.3337320.
  2. Pavleska, V. Rakovic, D. Denkovski, H. Gjoreski, “Split Learning for Human Activity Recognition” in Handbook of Neural Engineering, Volume 1: Signal Processing Strategies, Elsevier, 2024 (to appear)
  3. Kalabakov, B. Jovanovski, H. Gjoreski, V. Rakovic, D. Denkovski, B. Pfitzner, O. Konak, B. Arnrich “Federated Learning for Activity Recognition: A System Level Perspective,” in IEEE Access, vol. 11, pp. 64442-64457, 2023.
  4. Poposka, B. Jovanovski, V. Rakovic, D. Denkovski and Z. Hadzi-Velkov, “Resource Allocation of NOMA Communication Systems for Federated Learning,” in IEEE Communications Letters, vol. 27, no. 8, pp. 2108-2112, Aug. 2023.
  5. Cholakoska, B. Pfitzner, H. Gjoreski, V. Rakovic, D. Denkovski, B. Arnrich, M. Kalendar, “Federated Learning for Network Intrusion Detection in Ambient Assisted Living Environments,” IEEE Internet Computing, vol. 27, no. 4, pp. 15-22, July-Aug. 2023.
  6. Sazdov, M. Tashkovska, S. Krsteski, B. Jovanovski, S. Kalabakov, V. Rakovic, D. Denkovski, H. Gjoreski, “Prediction of Hospital Readmission using Federated Learning,” 30th International Conference on Systems, Signals and Image Processing (IWSSIP), Ohrid, North Macedonia, 2023, pp. 1-5.
  7. Rakovic. K.J. Hsu, K. Bhardwaj, A. Gavrilovska, L. Gavrilovska, “ShapeShifter: Resolving the Hidden Latency Contention Problem in MEC”, ACM/IEEE Symposium on Edge Computing, Seattle, USA, 2022.

Full list of papers