Dr Evangelos Vlachos

Research Associate



1.03 Alexander Graham Bell building

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Research Institute: 

  • Digital Communications

Research Theme: 

  • Communications
  • Signal and Image Processing
Dr Evangelos Vlachos
Dr Evangelos Vlachos


Evangelos Vlachos received the Diploma degree in Computer Engineering and Informatics, the MSc degree in Information Processing and Machine Learning and the Ph.D. degree in Signal Processing for Wireless Communications from University of Patras (UoP), Greece, in in 2005, 2009 and 2015, respectively. From 2015 to 2016 was a post-doctoral researcher at Laboratory of Signal Processing and Telecommunications in Computer Engeneering and Informatics, UoP, Greece working on distributed learning for signal processing over networks. During 2016 worked as a post-doctoral researcher at Visualization and Virtual Reality Group, UoP on graph signal processing and received best paper award from IEEE ICME2017. Since 2017, he is a post-doctoral researcher in signal processing for communications currently working at the Institute for Digital Communications (IDCOM), University of Edinburgh. His current focus is on the next-generation 5G wireless networks, developing efficient low-power and low-complexity techniques, suitable for the future millimetre wave massive MIMO systems. He has published 7 journals (5 as a first author) and 16 conferences (9 as a first author). He has participated in 6 research projects funded by EU.

Selected Publications:

1) E. Vlachos, George C. Alexandropoulos, and J. Thompson. Massive MIMO channel estimation for millimeter wave systems via matrix completion. IEEE Signal Processing Letters, 2018. URL: https://doi.org/10.1109/LSP.2018.2870533
2) E. Vlachos, A. S. Lalos, K. Moustakas, and K. Berberidis. Efficient graph-based matrix completion on incomplete animated models. In 2017 IEEE International Conference on Multimedia and Expo (ICME), pages 1548–1553, July 2017b. URL: http://dx.doi.org/10.1109/ICME.2017.8019502
3) E. Vlachos, A. Kaushik, and J. Thompson. Energy efficient transmitter with low resolution DACs for massive mimo with partially connected  hybrid architecture. In 2018 IEEE 87th Vehicular Technology Conference (VTC Spring), pages 1–5, June 2018. URL: http://dx.doi.org/10.1109/VTCSpring.2018.8417650
4) E. Vlachos, A. S. Lalos, and K. Berberidis. Low-complexity OSIC equalization for OFDM-based vehicular communications. IEEE Transactions on Vehicular Technology, PP (99):1–1, 2016. ISSN 0018-9545. URL: http://dx.doi.org/10.1109/TVT.2016.2598185
5) A. Lalos, I. Nikolas, E. Vlachos, and K. Moustakas. Compressed sensing for efficient encoding of dense 3D Meshes using model based Bayesian learning. IEEE Transactions on Multimedia, PP(99):1–1, 2016. ISSN 1520-9210. URL: http://dx.doi.org/10.1109/TMM.2016.2605927

Academic Qualifications: 

  • 2015: Ph.D. in Wireless Communications and Signal Processing, University of Patras, Greece.
  • 2009: M.Sc. in Signal Processing and Communications, University of Patras, Greece.
  • 2005 Diploma of Computer Engineering and Informatics, University of Patras, Greece.

Research Interests: 

statistical learning, distributed optimization, massive MIMO, millimeter wave communications, energy efficiency maximization