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KATSIS ATHANASIOS
PROFESSOR
RECTOR
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
Ε-mail: katsis (at) uop (dot) gr
Short CVProfessor Athanassios Katsis is a faculty member of the Department of Social and Education Policy at the University of the Peloponnese in Greece. His research covers the areas of Bayesian Statistics, optimal sample size calculations, statistical applications and education research. He has served as a faculty member at the University of the Aegean and has also taught at the University of Cyprus and the University of Toledo, Ohio. He has also been employed at the World Bank as a statistical consultant. Professor Katsis holds a doctoral and a masters degree in Statistics from the George Washington University in USA, where he studied with a full scholarship. Ηe finished his undegraduate studies in Mathematics at the National and Kapodistrian University of Athens in Greece.Professor Katsis has served as Head of the Department and Dean of the School of Social and Political Studies at the University of the Peloponnese. In December 2017, he was elected Rector of the University, where he was reelected for a second term in December 2022.
Scientific Interests: My research interests lie in the area of Bayesian Statistics, optimal sample size calculations, as well as applications in the educational research and telecommunications. Selected research projects:“Learning for Female African Migrants’ Solidarity: Help-Desks for Female African Migrants in the Eastern Mediterranean Region”, LLP-Grundtvig, 2013-15“BREAKing stereotypes through role models and promoting Roma integration in the labor market” DG Justice, 2017-2019“Adult Migrant Integration Experts” ADMIRE, Erasmus + / Strategic partnerships, 2017-2019“Enriching Teachers Skills in Digital Humanities Crowdsourcing”, Erasmus + / Strategic partnerships, 2021-2023 “Green collider: Introduction of sustainable thinking and Green Skills development through VET – business cooperation”, Erasmus + / Strategic partnerships, 2022-2024
Selected publications:
Selected publications:
1. Melanitis, M., Bithas, P.S., Katsis, A., Nistazakis, H.E. (2025). Designs and Optimization of an FSO Network Under Practical Considerations, Photonics, 12, 926. https://www.mdpi.com/2304-6732/12/9/926
2. Papadogiannis, I.; Vassilakis,C.; Wallace, M.; Katsis, A. (2024). Challenges and Trends in Student Evaluation of Teaching: Analysis of SET Data from the University of Peloponnese, Information. 2024; 15(9):576. https://doi.org/10.3390/info15090576
3. Papadogiannis, I.; Vassilakis,C.; Wallace, M.; Katsis, A. (2024). On the Quality and Validity of Course Evaluation Questionnaires Used in Tertiary Education in Greece. Trends in Higher Education, 3, 221–234, https://doi.org/10.3390/higheredu3020013
4. Bithas, P.S., Nistazakis, H.E., Katsis, A., Yang, L. (2024). Hybrid FSO/RF Communications in Space–Air–Ground Integrated Networks: A Reduced Overhead Link Selection Policy, Electronics, 13, 806, https://doi.org/10.3390/electronics13040806
5. Varotsos, G.K., Aidinis, K., Katsis, A., Nistazakis, H.E. (2023) Capacity Performance Analysis for Terrestrial THz Channels, Electronics, 12, 1336, https://doi.org/10.3390/electronics12061336
6. Gripeos, P.J.; Oreinos, D.; Kriempardis, D.; Tsigopoulos, A.D.; Kapotis, E.; Katsis, A.; Nistazakis, H.E. (2023). Dispersive FSO Performance Estimation with Gaussian Pulses and Laplace Modeled Time Jitter, Computation, 11, 6. https://doi.org/10.3390/computation11010006
7. Siokas, E., Xesternou, M., Katsis, A. (2022). Testing innovation management and technology transfer best practices within SMEs, Academia Letters, Article 5868. https://doi.org/10.20935/AL5868
8. Koutsoukis, N.S., Fakiolas, E., Katsis, A., Papadimitriou P. (2022). The EU as multidisciplinary education podium: Fusing contextual and decisional policy analytics, Policy Futures in Education, Vol, 20(5), 549-564, https://doi.org/10.1177%2F14782103211039488