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.
Academic Year 2021/2022
- DEPARTMENT OF ECONOMICS AND BUSINESS
Master's Degree in Data Science for Management - 1st Year
STATISTICAL LABORATORY - DEPARTMENT OF MATHEMATICS AND COMPUTER SCIENCES
Bachelor's Degree in Computer Science - 1st Year
PROGRAMMAZIONE II E LABORATORIO A - L
Academic Year 2020/2021
- DEPARTMENT OF ECONOMICS AND BUSINESS
Master's Degree in Data Science for Management - 1st Year
BASICS OF COMPUTING - DEPARTMENT OF MATHEMATICS AND COMPUTER SCIENCES
Bachelor's Degree in Computer Science - 1st Year
PROGRAMMAZIONE II E LABORATORIO A - L
Academic Year 2019/2020
- DEPARTMENT OF ECONOMICS AND BUSINESS
Master's Degree in Data Science for Management - 1st Year
STATISTICAL LABORATORY
Research interests lie in the fields of Computer Vision, Biometrics, Machine Learning and Multimedia.