Posts by Collection
portfolio
publications
FLAIRS
Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems
In the 33nd International Florida Artificial Intelligence Research Society Conference in Cooperation with AAAI, 2020
UMAP
FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems
In the 28th Conference on User Modeling, Adaptation and Personalization, 2020
KDD Workshop
Multi-sided Exposure Bias in Recommendation
In Workshop on Industrial Recommendation Systems in Conjuction with ACM KDD, 2020
CIKM
Feedback Loop and Bias Amplification in Recommender Systems
In the 29th ACM International Conference on Information and Knowledge Management, 2020
RecSys
The Connection between Popularity Bias, Calibration, and Fairness in Recommendation
In the Proceedings of the 14th ACM Conference on Recommender Systems, 2020
WSDM
Fairness-aware Recommendation in Multi-sided Platforms
In Proceedings of the 14th ACM International Conference on Web Search and Data Mining, 2021
TIST
Flatter is better: Percentile Transformations for Recommender Systems
ACM Transactions on Intelligent Systems and Technology, 12 no. 2, 2021
UMAP
Beyond Algorithmic Fairness in Recommender Systems
In Adjunct proceedings of the 29th ACM conference on user modeling, adaptation and personalization, 2021
UMAP
User-centered evaluation of popularity bias in recommender systems
In Proceedings of the 29th ACM conference on user modeling, adaptation and personalization, 2021
TOIS
A Graph-based Approach for Mitigating Multi-sided Exposure Bias in Recommender Systems
ACM Transactions on Information Systems, 40 no. 2, 2021
RecSys Workshop
Exposure-Aware Recommendation using Contextual Bandits
In 5th FAccTRec Workshop on Responsible Recommendation in conjunction with ACM RecSys 2022
RecSys Workshop
Career Path Recommendations for Long-term Income Maximization: A Reinforcement Learning Approach
In Workshop on Recommender Systems for Human Resources in conjunction with ACM RecSys 2023
RecSys Workshop
Fairness of Exposure in Dynamic Recommendation
In CONSEQUENCE Workshop on Causality, Counterfactuals, and Sequential Decision-Making in conjunction with ACM RecSys 2023
BNAIC
Potential Factors Leading to Popularity Unfairness in Recommender Systems: A User-Centered Analysis
In BNAIC Joint International Scientific Conference on AI and Machine Learning, 2023
RecSys Workshop
Correcting for Popularity Bias in Recommender Systems via Item Loss Equalization
In International Workshop on Recommender Systems for Sustainability and Social Good in conjunction with ACM RecSys 2024
CIKM
Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits
In the 33rd ACM International Conference on Information and Knowledge Management, 2024
RecSys
Mitigating Popularity Bias in Counterfactual Explanations using Large Language Models
In Proceedings of the 19th ACM Conference on Recommender Systems, 2025
RecSys
Opening the Black Box: Interpretable Remedies for Popularity Bias in Recommender Systems
In Proceedings of the 19th ACM Conference on Recommender Systems, 2025
RecSys Workshop
Using LLMs to Capture Users’ Temporal Context for Recommendation
In Workshop on Context-Aware Recommender Systems in conjunction with ACM RecSys 2025