Kofidis Eleftherios

Kofidis Eleftherios is an Associate Professor at the Department of Statistics and Insurance Science, University of Piraeus, Greece. He holds a Ph.D. in Computer Engineering and Informatics from the University of Patras (1996) and a Dipl. Ing. from the same institution (1990). His research focuses on signal processing, machine learning, digital communications, and biomedical applications, with a particular emphasis on tensor decompositions, filter bank multicarrier (FBMC) systems, and MIMO communication. He has contributed to over 70 peer-reviewed publications, including books and technical reports.

Teaching responsibilities include courses such as Numerical Analysis, Operations Research, and Topics in Data Science. His research interests span signal processing for communication systems, tensor-based algorithms for multidimensional data analysis, and applications in biomedical signal processing. He has collaborated extensively on projects such as the European FP7-ICT EMPhAtiC initiative, focusing on MIMO channel estimation and distributed systems.

Key research trends in his publications include: (1) tensor decomposition techniques for channel estimation and data fusion, (2) development of semi-blind receivers for MIMO systems, (3) analysis of filter bank-based multicarrier modulation for 5G/6G applications, and (4) biomedical signal processing using higher-order tensor methods. His recent work addresses challenges in RIS-enabled wireless systems and federated learning frameworks.

• Education:
  • Ph.D., Computer Engineering and Informatics, University of Patras, 1996
  • Dipl. Ing., Computer Engineering and Informatics, University of Patras, 1990
• Key Research Grants/Projects:
  • European FP7-ICT Project EMPhAtiC (MIMO channel estimation and distributed systems)
  • National and EU-funded initiatives on tensor-based signal processing
• Awards: None explicitly listed in the provided texts.
• Labs/Teams: Active in University of Piraeus's research groups on statistical signal processing and communications.

His work bridges theoretical advancements in tensor methods with practical applications in wireless communications and biomedical engineering, emphasizing solutions for next-generation communication systems and multidisciplinary data fusion challenges.