People

Miriam Rateike
(she/her)

​Saarland Informatics Campus
Building E1 1

Email: rateike [at] cs.uni-saarland.de

About me

Hello! I am Miriam Rateike (she/her). I am a PhD student at the Max-Planck-Institute for Intelligent Systems, Tübingen, and at the Graduate School of Computer Science of the University of Saarland (UdS). I am advised by Prof. Isabel Valera. In my research I focus on creating algorithms for fair decision making under realistic assumptions. I am particularly interested in the intersection of causality and fairness. In my free time I support TReND in Africa and am an active member of Femtec Alumnae e.V..

 

22/06 | I will be attending the FAccT-22 conference to present our recent paper in Seoul !

22/03 | Presentation Kausalität in der KI-Forschung – von Ursache und Wirkung at FTALive-22 conference | Presenter

21/12 | NeurIPS-21 workshop on Algorithmic Fairness through the Lens of Causality and Robustness | Co-organizer

21/10 | Panel discussion Fairness and discrimination in machine learning – possibilities and limits of artificial intelligence organized by University of Passau in cooperation with Femtec Alumnae e.V.. | Panelist

21/08 | OxML Summer School | Participant

21/07 | TReND Python Workshop for beginners | Co-organzier

21/07 | ELLIS Workshop on CausethicalML | Co-organizer

21/03 | Presentation Wenn der Algorithmus dich nicht für fähig hält – Ein Einblick in diskriminierende Algorithmen und fair AI at FTALive conference | Presenter

20/12 | NeurIPS-20 WiML Workshop | Poster presentation

 

Teaching Assistant

WS 12/22 | Elements of Machine Learning, CausethicalML Seminar

SS 21        | Machine Learning

WS 19/21 | Elements of Machine Learning

Publications

2022

Rateike, Miriam; Majumdar, Ayan; Mineeva, Olga; Gummadi, Krishna P.; Valera, Isabel

Don’t Throw It Away! The Utility of Unlabeled Data in Fair Decision Making Inproceedings

In: 2022 ACM Conference on Fairness, Accountability, and Transparency, pp. 1421–1433, Association for Computing Machinery, Seoul, Republic of Korea, 2022, ISBN: 9781450393522.

Abstract | Links | BibTeX

2021

Sánchez-Martín, Pablo; Rateike, Miriam; Valera, Isabel

VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries Journal Article

In: CoRR, vol. abs/2110.14690, 2021.

Links | BibTeX