Tom Sühr is a doctoral candidate at the Max Planck Institute for Intelligent Systems in the Human Aspects of Machine Learning group lead by Samira Samadi. He completed his Msc. in Information Systems Management at TU Berlin while being a research assistant at Harvard Business School. He is currently working on research projects with Harvard University and the University of Tübingen. During his undergraduate studies he was a research intern at the Max Planck Institute for Software Systems advised by Krishna Gummadi and Asia Biega as well as a student researcher at the chair of complex distributed systems (CIT) advised by Meike Zehlike and Carlos Castillo. He is broadly interested in algorithmic fairness, fair systems and economic implications of algorithmic decision making.


Socially Responsible Language Modelling Research (SoLaR) 2023 at NeurIPS 2023
Does fair ranking improve minority outcomes? understanding the interplay of human and algorithmic biases in online hiring
T Sühr, S Hilgard, H Lakkaraju
Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 989-999

Fair Top-k Ranking with multiple protected groups
M Zehlike, T Sühr, R Baeza-Yates, F Bonchi, C Castillo, S Hajian
Information Processing & Management 59 (1), 102707

A Note on the Significance Adjustment for FA* IR with Two Protected Groups
M Zehlike, T Sühr, C Castillo
arXiv preprint arXiv:2012.12795

Fairsearch: A tool for fairness in ranked search results
M Zehlike, T Sühr, C Castillo, I Kitanovski
Companion Proceedings of the Web Conference 2020, 172-175

Two-sided fairness for repeated matchings in two-sided markets: A case study of a ride-hailing platform
T Sühr, AJ Biega, M Zehlike, KP Gummadi, A Chakraborty
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining