Hubert Baniecki

University of WarsawWarsaw University of TechnologyMI².AI

h.baniecki (at) uw.edu.pl

I am a 2nd year PhD student in Computer Science at the University of Warsaw advised by Przemyslaw Biecek. Prior, I did my MSc (2022) and BSc (2021) in Data Science at Warsaw University of Technology, Poland.

My main research interest is explainable machine learning, with particular emphasis on adversarial attacks & explanation evaluation. I also care about human-model interaction with applications in medicine, and support the development of several open-source Python & R packages for building predictive models responsibly.

I received the 2022 John M. Chambers Statistical Software Award.


recent news [more]

2024 May A paper On the robustness of global feature effect explanations is accepted at ECML PKDD 2024.
2024 Apr A paper Performance is not enough: The story told by a Rashomon quartet is accepted for publication in the Journal of Computational and Graphical Statistics.
2024 Apr Two papers on Red teaming are accepted at ICLR 2024 Workshops and CVPR 2024 Workshops .
2024 Mar I stay in Germany until June for a 4-month research visit at LMU Munich hosted by Bernd Bischl and Giuseppe Casalicchio.
2024 Feb A paper Adversarial attacks and defenses in explainable artificial intelligence: A survey is accepted for publication in Information Fusion.

selected publications [full list]

    1. Adversarial attacks and defenses in explainable artificial intelligence: A survey
      H. Baniecki, P. Biecek
      Information Fusion, 2024
      Review of adversarial attacks on explanations and how to defend them.
    2. The grammar of interactive explanatory model analysis
      H. Baniecki, D. Parzych, P. Biecek
      Data Mining and Knowledge Discovery, 2023
      Interactive explanation of a model improves the performance of human decision making.
    3. Fooling partial dependence via data poisoning
      H. Baniecki, W. Kretowicz, P. Biecek
      ECML PKDD 2022
      Feature effect explanations can be manipulated in an adversarial manner.
    4. dalex: Responsible machine learning with interactive explainability and fairness in Python
      H. Baniecki, W. Kretowicz, P. Piatyszek, J. Wisniewski, P. Biecek
      Journal of Machine Learning Research, 2021
      2022 John M. Chambers Statistical Software Award