SCARPA FABIO

Ufficio:

Telefono:

E-mail: fabio.scarpa@unipd.it

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2023

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2023

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2023

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2022

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2022

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2022

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2022

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2021

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2021

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2021

Bioimmagini
Codice: INP9086343 / Ordinamento: 2020 / Anno Accademico: 2021

Elaborazione di dati, segnali e immagini biomediche
Codice: INP3052642 / Ordinamento: 2011 / Anno Accademico: 2017

In October 2005 I received the master’s degree (five years graduate program) in Electronic Engineering at the University of Padova. My thesis received the “Premio di Laurea inTESI 2005” prize.

From January 2006 to December 2008, I was Ph.D. student in BioEngineering at the Department of Information Engineering, University of Padova.
I defended the thesis “Automatic analysis of confocal images of the cornea” in March 2009.

I was Software Engineer at Nidek Technologies (Albignasego, Padova) and at D-EYE srl (Padova).

I was Postdoctoral Fellow at the Department of Developmental Psychology and at the Department of Information Engineering, University of Padova.

I'm currently Assistant Professor at the Department of Information Engineering, University of Padova.

My research and professional activity deals with the development of innovative algorithms for image processing, signal processing and data analysis in the biomedical field. My main interests concern methods for image enhancement, segmentation and classification, neural networks, machine learning, deep learning, artificial intelligence, modeling of physiological components, entropy and fractal measures of bio-signals.