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)

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

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

Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring. - Tom Sühr; Sophie Hilgard; Himabindu Lakkaraju (AIES, 2021)

Image-Text Rematching for News Items using Optimized Embeddings and CNNs in MediaEval NewsImages 2021. - Tom Sühr; Ajay Madhavanr; Nasim Jamshidi Avanaki; René Berk; Andreas Lommatzsch (MediaEval, 2021)

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)

Do personality tests generalize to Large Language Models? - Florian E. Dorner; Tom Sühr; Samira Samadi; Augustin Kelava (CoRR, 2023)

A Dynamic Model of Performative Human-ML Collaboration: Theory and Empirical Evidence. - Tom Sühr; Samira Samadi; Chiara Farronato (CoRR, 2024)

Online Decision Deferral under Budget Constraints. - Mirabel Reid; Tom Sühr; Claire Vernade; Samira Samadi (CoRR, 2024)

Stop Evaluating AI with Human Tests, Develop Principled, AI-specific Tests instead. - Tom Sühr; Florian E. Dorner; Olawale Salaudeen; Augustin Kelava; Samira Samadi (CoRR, 2025)