KInIT is a European Centre of Excellence in AI supported by

Research Group

Web & User Data Processing

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Bio
Projects
Publications

Matúš Tibenský

Research areas: artificial intelligence, machine learning, recommendation systems, bayesian statistics, human interactions with AI systems

Position: AI Specialist

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Matus holds Master’s degree in Mathematics from Comenius University in Bratislava, Engineer’s degree in Statistics from Economic University in Bratislava and Doctoral degree in Applied Mathematics from Technical University in Bratislava. Besides his position at KINIT he is still teaching and supervising students’ theses at Technical University in Bratislava.

His publishing history contains contributions in image processing, financial mathematics, geology and machine learning, prominently.

On top of his career in research he has been contributing to the machine learning community in the industry for more than 10 years. His journey started as a Predictive Analyst in an insurance industry, where he was developing and maintaining classic ML algorithms for regression and classification tasks. This was followed by the position in consultancy, where he focused on Natural Language Processing problems in Slovak language. Before joining KINIT he worked as a Senior Data Scientist in the start -up ecosystem, where his main interests were recommendation systems. He develops algorithms in energy pricing at the moment.

At KInIT, Matus focuses on auditing social networks’ recommendation systems with special focus on this systems’ impact on users and society at all.

Selected achievements

Co-author of scientific papers accepted to UMAP, SIGIR or FAccT conferences.

Selected activities

University lectures in mathematical analysis, functional analysis, financial mathematics and statistics and probability theory.

Selected Projects

AI-Auditology: Social Media AI Algorithms Auditing

The goal of the AI-Auditology project is to fundamentally change the oversight of social media AI algorithms, like recommender systems or search engines, and their tendencies to spread and promote…

Selected Publications

Revisiting Algorithmic Audits of TikTok: Poor Reproducibility and Short-term Validity of Findings

Mosnar, M., Skurla, A., Pecher, B., Tibensky, M., Jakubčík, J., Bindas, A., Sakalík, P., Srba, I. – SIGIR ’25: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval,

Social media platforms are constantly shifting towards algorithmically curated content based on implicit or explicit user feedback. Regulators, as well as researchers, are calling for systematic social media algorithmic audits…

The DSA’s Blind Spot: Algorithmic Audit of Advertising and Minor Profiling on TikTok

Solarova, S., Mosnar, M.,Tibensky, M., Jakubcik, J., Bindas, A., Liska, S., Hossner, F., Mesarcik, M., Srba, I. – Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’26),

Solarova, S., Mosnar, M., Tibensky, M., Jakubcik, J., Bindas, A., Liska, S., Hossner, F., Mesarcik, M., Srba, I. Adolescents spend an increasing amount of their time in digital environments where…

Algorithmic Audit of Personalisation Drift in Polarising Topics on TikTok

Pecher, B., Bindas, A., Jakubcik, J., Tuna, M., Tibensky, M., Liska, S., Sakalik, P., Suty, A., Mosnar, M., Hossner, F., Srba, I. – Proceedings of the 34th ACM Conference on User Modeling, Adaptation and Personalization,

Pecher, B., Bindas, A., Jakubcik, J., Tuna, M., Tibensky, M., Liska, S., Sakalik, P., Suty, A., Mosnar, M., Hossner, F., Srba, I. Social media platforms have become an integral part…

Selected student supervising

Hannah Kuklovská: Social media audit visualisation template, SvF STU BA, 2026.

Hana Puváková: P-hacking, SvF STU BA, 2026.