FA*IR: A Fair Top-k Ranking Algorithm. - Meike Zehlike; Francesco Bonchi; Carlos Castillo 001; Sara Hajian; Mohamed Megahed; Ricardo Baeza-Yates (CIKM, 2017)

Two-Sided Fairness for Repeated Matchings in Two-Sided Markets: A Case Study of a Ride-Hailing Platform. - Tom Sühr; Asia J. Biega; Meike Zehlike; Krishna P. Gummadi; Abhijnan Chakraborty (KDD, 2019)

Reducing Disparate Exposure in Ranking: A Learning To Rank Approach. - Meike Zehlike; Carlos Castillo 001 (WWW, 2020)

FairSearch: A Tool For Fairness in Ranked Search Results. - Meike Zehlike; Tom Sühr; Carlos Castillo 001; Ivan Kitanovski (WWW (Companion Volume), 2020)

Towards a Flexible Framework for Algorithmic Fairness. - Philipp Hacker; Emil Wiedemann; Meike Zehlike (CoRR, 2020)

A Note on the Significance Adjustment for FA*IR with Two Protected Groups. - Meike Zehlike; Tom Sühr; Carlos Castillo 001 (CoRR, 2020)

Matching code and law: achieving algorithmic fairness with optimal transport. - Meike Zehlike; Philipp Hacker; Emil Wiedemann (Data Min. Knowl. Discov., 2020)

Fairness in Ranking: A Survey. - Meike Zehlike; Ke Yang 003; Julia Stoyanovich (CoRR, 2021)

Fair ranking: a critical review, challenges, and future directions. - Gourab K. Patro; Lorenzo Porcaro; Laura Mitchell; Qiuyue Zhang; Meike Zehlike; Nikhil Garg 001 (FAccT, 2022)

Fair Top-k Ranking with multiple protected groups. - Meike Zehlike; Tom Sühr; Ricardo Baeza-Yates; Francesco Bonchi; Carlos Castillo 001; Sara Hajian (Inf. Process. Manag., 2022)

Fairness in Rankings. - Meike Zehlike (2022)

Fairness in Rankings. - Meike Zehlike (Ausgezeichnete Informatikdissertationen, 2022)

Body Measurement Prediction Fairness. - Alex Loosley; Amrollah Seifoddini; Alessandro Canopoli; Meike Zehlike (EWAF, 2023)

Fairness in Ranking: From Values to Technical Choices and Back. - Julia Stoyanovich; Meike Zehlike; Ke Yang 003 (SIGMOD Conference Companion, 2023)

Tutorials at The Web Conference 2023. - Valeria Fionda; Olaf Hartig; Reyhaneh Abdolazimi; Sihem Amer-Yahia; Hongzhi Chen; Xiao Chen 016; Peng Cui 001; Jeffrey Dalton 001; Xin Luna Dong; Lisette Espín-Noboa; Wenqi Fan; Manuela Fritz; et al. (WWW (Companion Volume), 2023)

Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems. - Meike Zehlike; Ke Yang 003; Julia Stoyanovich (ACM Comput. Surv., 2023)

Fairness in Ranking, Part I: Score-Based Ranking. - Meike Zehlike; Ke Yang 003; Julia Stoyanovich (ACM Comput. Surv., 2023)

Beyond incompatibility: Trade-offs between mutually exclusive fairness criteria in machine learning and law. - Meike Zehlike; Alex Loosley; Håkan Jonsson; Emil Wiedemann; Philipp Hacker (Artif. Intell., 2025)