UOP staff
ΖΕΡΒΑΣ ΠΑΝΑΓΙΩΤΗΣ
ΕΠΙΚΟΥΡΟΣ ΚΑΘΗΓΗΤΗΣ (ΜΟΝΙΜΟΣ)
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
Ε-mail: p.zervas (at) uop (dot) gr
Γραφείο: K2.04B
Ώρες Γραφείου: Τετάρτη και Παρασκευή 9.00πμ - 12.30πμ - (Συνίσταται πρότερη επικοινωνία μέσω email)
Σύντομο Βιογραφικό Σημείωμα

Ο Παναγιώτης Ζέρβας είναι Επίκουρος Καθηγητής του Τμήματος Ηλεκτρολόγων Μηχανικών & Μηχανικών Η/Υ του Πανεπιστημίου Πελοποννήσου με γνωστικό αντικείμενο “Πληροφοριακά Συστήματα Ήχου”. Από το 2008 μέχρι το 2020 ήταν μέλος ΔΕΠ του τμήματος Μουσικής Τεχνολογίας και Ακουστικής του Ελληνικού Μεσογειακού Πανεπιστημίου.

Είναι απόφοιτος του Τμήματος Ηλεκτρολόγων Μηχανικών και Τεχνολογίας ΗΥ του Πανεπιστημίου Πατρών από το 1998. Το 2000 έλαβε μεταπτυχιακό δίπλωμα ειδίκευσης (MSc) στα “Συστήματα Επεξεργασίας Σημάτων & Εικόνων”, από το Τμήμα Μηχανικών ΗΥ & Πληροφορικής του Πανεπιστημίου Πατρών. Το 2008 έλαβε διδακτορικό δίπλωμα από το τμήμα Ηλεκτρολόγων Μηχανικών & Τεχνολογίας ΗΥ του Πανεπιστημίου Πατρών με τίτλο “Μοντελοποίηση προσωδίας ομιλίας Ελληνικής Γλώσσας με εφαρμογές στην σύνθεση ομιλίας από κείμενο”.

Έχει διδάξει μαθήματα σε προπτυχιακό και μεταπτυχιακό επίπεδο στο αντικείμενο της Ψηφιακής Επεξεργασίας Ήχου, Εφαρμοσμένης Μηχανικής Μάθησης, Προγραμματισμού Εφαρμογών Ήχου, και Μικροεπεξεργαστών. Έχει συμμετάσχει σε πλήθος από ερευνητικά και αναπτυξιακά έργα. Έχει πλήθος δημοσιεύσεων σε διεθνή περιοδικά, κεφάλαια σε συλλογικούς τόμους και σε πρακτικά διεθνών συνεδρίων με κριτές. Έχει συμμετάσχει σε επιστημονικές και οργανωτικές επιτροπές συνεδρίων και επιστημονικών εκδηλώσεων. Είναι μέλος του Ελληνικού Ινστιτούτου Ακουστικής (ΕΛΙΝΑ).

Short CVPanagiotis Zervas is an Assistant Professor at the Department of Electrical and Computer Engineering of the University of Peloponnese in the field of “Audio Information Systems”. From 2008 to 2020 he was a faculty member of the Department of Music Technology and Acoustics of the Hellenic Mediterranean University.
He is a graduate of the Department of Electrical Engineering and Computer Technology of the University of Patras since 1998. In 2000 he received a master’s degree (MSc) in “Signal & Image Processing Systems” from the Department of Computer Engineering & Informatics of the University of Patras. In 2007 he received a doctorate from the Department of Electrical Engineering & Computer Technology of the University of Patras entitled “Prosody Modelling of Greek Language with applications in Text to Speech Systems”.
He has taught undergraduate and graduate courses in the field of Digital Audio Signal Processing, Applied Machine Learning, Audio Application Programming, Microprocessors and Educational Technology His research interests focus on audio signal processing and pattern recognition, speech recognition and synthesis, natural language processing, music information retrieval and real-time network music performance. He has participated in several research and development projects. He has published numerous articles in international journals, chapters in collective volumes and in the proceedings of international conferences. He has participated in scientific and organizational committees of conferences and scientific events. He is a member of the Hellenic Institute of Acoustics (ELINA).
Επιστημονικά Ενδιαφέροντα:
  • Επεξεργασία σήματος και αναγνώριση προτύπων σε ακουστικά σήματα
  • Επικοινωνία ανθρώπου μηχανικής, αναγνώριση/σύνθεση ομιλίας, επεξεργασία φυσικής γλώσσας
  • Ακουστική ανίχνευση (παρακολούθηση ηχορύπανσης, αναγνώριση ακουστικών γεγονότων) σε έξυπνα περιβάλλοντα με μεθόδους βαθιάς μάθησης σε ενσωματωμένες συσκευές συνδεδέμενες με τεχνολογίες διαδικτύου των πραγμάτων
  • Αυτόματη ανάκτηση μουσικής πληροφορία, διαδικτυακή μουσική εκτέλεση
Science Interest:
  • Signal processing and pattern recognition in audio signals
  • Engineering human communication, speech recognition / synthesis, natural language processing
  • Acoustic detection (noise monitoring, acoustic event detection) in intelligent environments with deep learning methods on embedded devices connected to internet technologies of things
  • Automatic music information retrieval, online music performance