Alessandro ORTIS
Alessandro Ortis is a Assistant Professor at the Department of Mathematics and Computer Science at the University of Catania, where he also serves as teacher of Programmazione 2 (BD in Computer Science). His research interests include computer vision, multimedia and adversarial machine learning, where he has worked on a number of problems, including first person vision, crowdsourcing and multimodal analysis, visual sentiment analysis and physiological signal analysis. He received his PhD in Mathematics and Comptuer Science in 2019, part of the PhD research has been spent at the Imperial College in London, under the supervision of Prof. Catarina Sismeiro. Alessandro is an active member of several scientific associations and societeies, serves as editor and reviewer for several journals and is organizer of several international scientific events, including conferences, challenges, workshops and special issues. Member of IPLAB (https://iplab.dmi.unict.it/), IEEE Senior Member and member of the IEEE Signal Processing Society.
His current work focuses on deepfake and adversarial learning toward the definition of adversarially robust models.
Alessandro is co-author of more than 20 papers published in international journals, more than 40 proceedings in conferences, and co-inventor of 1 International Patent.
Anno accademico 2021/2022
- DIPARTIMENTO DI ECONOMIA E IMPRESA
Corso di laurea magistrale in Data Science for Management - 1° anno
STATISTICAL LABORATORY - DIPARTIMENTO DI MATEMATICA E INFORMATICA
Corso di laurea in Informatica - 1° anno
PROGRAMMAZIONE II E LABORATORIO A - L
Anno accademico 2020/2021
- DIPARTIMENTO DI ECONOMIA E IMPRESA
Corso di laurea magistrale in Data Science for Management - 1° anno
BASICS OF COMPUTING - DIPARTIMENTO DI MATEMATICA E INFORMATICA
Corso di laurea in Informatica - 1° anno
PROGRAMMAZIONE II E LABORATORIO A - L
Anno accademico 2019/2020
- DIPARTIMENTO DI ECONOMIA E IMPRESA
Corso di laurea magistrale in Data Science for Management - 1° anno
STATISTICAL LABORATORY
Ricerca in ambito della Computer Vision, Biometria, Machine Learning e Multimedia.