We are pleased to invite you to the trial lecture and public defence of Anastasiia Klimashevskaia, PhD candidate at SFI MediaFutures.

Date: 15 December
Venue: Ulrikes Aula, University of Bergen

Time: To be confirmed

PhD Thesis:
Beyond Popularity: Investigating and Mitigating Bias in Recommender Systems

Thesis Summary:
Recommender systems are powerful tools shaping what users see and engage with online. However, they often suffer from popularity bias, where already popular items are disproportionately promoted while niche content remains underrepresented. This bias reduces diversity, user satisfaction, and fairness across platforms.

In her doctoral work, Anastasiia Klimashevskaia examines the causes and effects of popularity bias through a comprehensive literature review, explores debiasing strategies using real-world datasets, and evaluates their performance in an online A/B test within a live recommender system.

Her research further investigates how popularity bias interacts with other algorithmic biases and proposes novel mitigation strategies based on alternative theoretical frameworks. The findings shed light on the trade-offs between fairness, diversity, and recommendation quality—contributing to the creation of more equitable recommender systems.

All are warmly welcome to attend and take part in celebrating Anastasiia’s important milestone.