ΚΑΤΣΗΣ ΑΘΑΝΑΣΙΟΣ
ΚΑΘΗΓΗΤΗΣ
ΠΡΥΤΑΝΗΣ
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
ΤΜΗΜΑ ΚΟΙΝΩΝΙΚΗΣ ΚΑΙ ΕΚΠΑΙΔΕΥΤΙΚΗΣ ΠΟΛΙΤΙΚΗΣ - ΚΟΡΙΝΘΟΣ
Ε-mail: katsis (at) uop (dot) gr
Γραφείο: Πρυτανεία Πανεπιστημίου, Τρίπολη
Ώρες Γραφείου: Κατόπιν συνεννόησης - (Συνίσταται η προηγούμενη συνεννόηση)
Σύντομο Βιογραφικό ΣημείωμαΟ Θανάσης Κατσής είναι Καθηγητής στο Τμήμα Κοινωνικής και Εκπαιδευτικής Πολιτικής του Πανεπιστημίου Πελοποννήσου. Το γνωστικό του αντικείμενο είναι στατιστικές εφαρμογές στην εκπαιδευτική έρευνα. Έχει διατελέσει μέλος ΔΕΠ στο Πανεπιστήμιο Αιγαίου ενώ έχει επίσης διδάξει στο Πανεπιστήμιο Κύπρου και στο Πανεπιστήμιο του Toledo στο Ohio των ΗΠΑ. Έχει επίσης εργασθεί ως στατιστικός σύμβουλος στην Παγκόσμια Τράπεζα.
Κατέχει διδακτορικό και μεταπτυχιακό τίτλο σπουδών στη Στατιστική από το George Washington University των ΗΠΑ όπου σπούδασε με ολική υποτροφία του Πανεπιστημίου ενώ τελείωσε τις προπτυχιακές του σπουδές στο Τμήμα Μαθηματικών του Εθνικού και Καποδιστριακού Πανεπιστημίου Αθηνών.
Έχει υπηρετήσει ως πρόεδρος του Τμήματος και Κοσμήτορας της Σχολής Κοινωνικών και Πολιτικών Επιστημών ενώ από το Δεκέμβριο του 2017 είναι Πρύτανης του Πανεπιστημίου Πελοποννήσου, θέση στην οποία επανεξελέγη το Δεκέμβριο του 2022.
Short CV
Professor 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.
Γνωστικό Αντικείμενο: Στατιστική με Έμφαση στην Εκπαιδευτική Έρευνα [ ΦΕΚ 46/Γ΄/21-01-2013 ]
Επιστημονικά Ενδιαφέροντα:
Τα ερευνητικά μου ενδιαφέροντα είναι στην περιοχή της Στατιστικής κατά Bayes, στον υπολογισμό του βέλτιστου μεγέθους δείγματος και στις εφαρμογές στην Εκπαιδευτική Έρευνα και στις Τηλεπικοινωνίες.
Science Interest:
My research interests lie in the area of Bayesian Statistics, optimal sample size calculations, as well as applications in the educational research and telecommunications.
Επιλεγμένες Δημοσιεύσεις:
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
Selected publications: