About
I am a PhD student at the Max Planck Institute for Software Systems. My advisor is Krishna P. Gummadi.
My research interests are in the area of fairness in Machine Learning as well as understanding the effects of algorithmic decision making and digitalization on society.
I pursued my undergraduate studies in computer science at Saarland University.
Publications
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Measuring Representational Robustness of Neural Networks Through Shared Invariances
Vedant Nanda, Till Speicher, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Adrian Weller
ICML 2022, accepted as oral presentation
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Unifying Model Explainability and Robustness via Machine-Checkable Concepts
Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Muhammad Bilal Zafar
Preprint
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A Unified Approach to Quantifying Algorithmic Unfairness:
Measuring Individual & Group Unfairness via Inequality Indices
Till Speicher, Hoda Heidari, Nina Grgic-Hlaca, Krishna P. Gummadi, Adish Singla, Adrian Weller, Muhammad Bilal Zafar
KDD '18: The 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2018, London, United Kingdom, August 2018
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Potential for Discrimination in Online Targeted Advertising
Till Speicher, Muhammad Ali, Giridhari Venkatadri, Filipe Nunes Ribeiro, George Arvanitakis, Fabrício Benevenuto, Krishna P. Gummadi, Patrick Loiseau, Alan Mislove
Conference on Fairness, Accountability, and Transparency - FAT* 2018, New York, US, February 2018.
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Reliable Learning by Subsuming a Trusted Model:
Safe Exploration of the Space of Complex Models
Till Speicher, Muhammad Bilal Zafar, Krishna P. Gummadi, Adish Singla and Adrian Weller
Reliable Machine Learning in the Wild - ICML 2017 Workshop, Sydney, Australia, August 2017.
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A Generalized Language Model as the Combination of Skipped n-grams and Modified Kneser-Ney Smoothing
Rene Pickhardt, Thomas Gottron, Martin Körner, Paul Georg Wagner, Till Speicher, Steffen Staab
ACL 2014, Baltimore, US, June 2014.