Prof. Dr. Gjergji Kasneci
Academic Career and Research Areas
Prof. Kasneci's (*1980) research area is "Responsible Data Science". In particular, Prof. Kasneci focuses on transparency, robustness, bias, and fairness in machine learning algorithms. Ethical, legal, and societal issues are at the forefront of his research, with the goal of using data science and artificial intelligence responsibly for the benefit of individuals and society.
Prof. Kasneci obtained his MSc of Computer Science and Mathematics from the University of Marburg in 2005 and his PhD from the University of Saarland (while at the Max Planck Institute) in 2009. He then worked at Microsoft Research Cambridge, the Hasso Plattner Institute, and SCHUFA Holding AG, where he served as CTO from 2017 to 2022. Between 2018 and 2023, he led the Data Science and Analytics Group at the University of Tübingen as an Honorary Professor. In 2023, Prof. Kasneci was appointed Professor of Responsible Data Science at TUM.
Awards
- Honorary Professorship from the University of Tübingen (2019)
- Seoul Test of Time Award by the International World Wide Web Conference Committee, international recognition for one of the most influential articles on Knowledge Extraction and Organization (2018)
Key Publications (all publications)
Rong, Y., Leemann, T., Borisov, V., Kasneci, G., & Kasneci, E. (2022). A consistent and efficient evaluation strategy for attribution methods. In Proceedings of the International Conference on Machine Learning 2022 (18770-18795).
AbstractPawelczyk, M., Broelemann, K., & Kasneci, G.: Learning model-agnostic counterfactual explanations for tabular data. In Proceedings of The Web Conference 2020 (pp. 3126-3132).
AbstractKasneci, G., Ramanath, M., Sozio, M., Suchanek, F. M., & Weikum, G.: Star: Steiner-tree approximation in relationship graphs. In 2009 IEEE 25th International Conference on Data Engineering (pp. 868-879).
AbstractKasneci, G., Suchanek, F. M., Ifrim, G., Ramanath, M., & Weikum, G.: Naga: Searching and ranking knowledge. In 2008 IEEE 24th International Conference on Data Engineering (pp. 953-962).
AbstractSuchanek, F. M., Kasneci, G., & Weikum, G.: "Yago: a core of semantic knowledge". In Proceedings of the 16th International Conference on World Wide Web 2007 (pp. 697-706).
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