Research Group
Róbert Móro
Research areas: artificial intelligence, machine learning, user modeling, personalization, misinformation detection, eye tracking
Position: Researcher
Róbert works as a senior researcher focusing on user modeling, personalization and machine learning. Lately, he has been researching how to characterize, detect and mitigate misinformation. In 2017, he obtained a Doctoral degree in Intelligent Software Systems from the Slovak University of Technology in Bratislava, where he also worked as an Assistant Professor from 2017 to 2020, teaching Intelligent Data Analysis. While at the university, he was a member of the PeWe (Personalized Web) research group led by Prof. Bieliková and worked at the User Experience and Interaction Research Center.
Róbert has co-operated in several international research projects with the University of Lugano, University of British Columbia, and Bar-Ilan University. He has worked in more than 10 national and international research projects and has been involved in multiple industry projects.
Professional Service
Conferences and Workshops: UMAP (Conference on User Modeling, Adaptation and Personalization), ETRA (ACM Symposium on Eye Tracking Research and Applications), IJCAI (International Joint Conference on Artificial Intelligence)
Journals: Journal of Web Engineering, Journal of Eye Movement Research
Professional Societies: ACM (Professional member), ACM Slovakia Chapter (Secretary), Slovak.AI (Supporter)
Selected Projects
Misinformation Detection in Healthcare Domain
APVV SK-IL-RD-18-0004. 2018-2020, Partner: Bar Ilan University (prof. Sarit Kraus), Bielikova, M. – principal investigator
Automated Recognition of Antisocial Behaviour in Online Communities
APVV-17-0267. 2018-2020, Partners: Comenius University in Bratislava, Technical University in Kosice, Navrat, P. – principal investigator
Selected Publications
Analysis of selected regulations proposed by the European Commission and technological solutions in relation to the dissemination of disinformation and the behaviour of online platforms
Mesarcik, M., Moro, R., Kompan, M., Podrouzek, J., Simko, J., Bielikova, M. This study was prepared by the Kempelen Institute of Intelligent Technologies based on an order from Miriam Lexmann,…
An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes
The negative effects of misinformation filter bubbles in adaptive systems have been known to researchers for some time. Several studies investigated, most prominently on YouTube, how fast a user can…
Quantitative and qualitative analysis of linking patterns of mainstream and partisan online news media in Central Europe
Hrckova, A., Moro, R., Srba, I., Bielikova, M. Purpose Partisan news media, which often publish extremely biased, one-sided or even false news, are gaining popularity world-wide and represent a major…
Selected Student Supervising
Master
- Hucko Andrej – Explainable Fake News Detection Method. Defended 2020
- Kuchár Vladimír – Automatic text comprehension detection. Defended 2019
- Mokrý Martin – Identification of the user skill on the Web based on patterns in eye tracking data. Defended 2018
Bachelor
- Štefancová Elena – User Experience and Emotions. Defended 2017. Results published at ADBIS 2018.
- Berger Patrik – Mind-Controlled Application. Defended 2016. Results published at SMAP 2017.
- Matlovič Tomáš – Mind-Controlled Application. Defended 2016. Results published at SMAP 2016.