I am an assistant professor at Johannes Kepler University - JKU. Prior to it, I was a post doctoral researcher at Idiap Research Institute (affiliated with EPFL), and a PhD candidate at TU Wien. I explore deep learning methods in natural language processing and information retrieval, with a focus on fairness and algorithmic bias mitigation.
Univ. Ass., Dr. Navid Rekab-saz
Assistant Professor
Unlearning Protected User Attributes in Recommendations with Adversarial Training
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022
ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations
Proceedings of the 16th ACM Conference on Recommender Systems (RecSys), 2022
Investigating Gender Fairness of Recommendation Algorithms in the Music Domain
Information Processing & Management, 2021
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?
Proceedings of the 15th ACM Conference on Recommender Systems (RecSys), 2021
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models
Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval, 2021
