PhD Award Meike Nauta

Meike Nauta has been awarded the Overijssel PhD Award for her outstanding dissertation, “Explainable AI and Interpretable Computer Vision – From Oversight to Insight.” The award recognizes Nauta’s innovative research, which focuses on making AI systems more transparent and interpretable, especially in the field of computer vision. Her work provides new methods to understand and trust AI decisions, bridging the gap between complex models and human understanding.

Congratulations, Meike, on this well-deserved honor! Read more about the award here.

Key Publications

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1. Meike Nauta, Jan Trienes, Shreyasi Pathak, Elisa Nguyen, Michelle Peters, Yasmin Schmitt, Jörg Schlötterer, Maurice van Keulen, and Christin Seifert. From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI. ACM Comput. Surv.. 2023.
   BibTeX

   @article{Nauta2023_csur_evaluating-xai-survey,
     author = {Nauta, Meike and Trienes, Jan and Pathak, Shreyasi and Nguyen, Elisa and Peters, Michelle and Schmitt, Yasmin and Schl\"{o}tterer, J\"{o}rg and van Keulen, Maurice and Seifert, Christin},
     journal = {ACM Comput. Surv.},
     title = {{From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI}},
     year = {2023},
     issn = {0360-0300},
     month = feb,
     address = {New York, NY, USA},
     comment = {https://utwente-dmb.github.io/xai-papers/},
     doi = {10.1145/3583558},
     file = {:own-pdf/Nauta2023_csur_evaluating-xai-survey_preprint-incl-suppl.pdf:PDF},
     keywords = {explainability, explainable AI, explainable artificial intelligence, XAI, interpretable machine learning, interpretability, quantitative evaluation methods, evaluation},
     publisher = {Association for Computing Machinery}
   }
   

2. Meike Nauta, Johannes H. Hegeman, Jeroen Geerdink, Jörg Schlötterer, Maurice van Keulen, and Christin Seifert. Interpreting and Correcting Medical Image Classification with PIP-Net. ECAI International Workshop on Explainable and Interpretable Machine Learning (XI-ML). 2023.
   BibTeX

   @inproceedings{Nauta2023_xml_pipnet-medical,
     author = {Nauta, Meike and Hegeman, Johannes H. and Geerdink, Jeroen and Schl\"{o}tterer, J\"{o}rg and {van Keulen}, Maurice and Seifert, Christin},
     booktitle = {ECAI International Workshop on Explainable and Interpretable Machine Learning (XI-ML)},
     title = {{Interpreting and Correcting Medical Image Classification with PIP-Net}},
     year = {2023},
     address = {Cham},
     pages = {198--215},
     publisher = {Springer Nature Switzerland},
     doi = {10.1007/978-3-031-50396-2_11},
     file = {:own-pdf/Nauta2023_xml_pipnet-medical_preprint.pdf:PDF},
     url = {https://arxiv.org/abs/2307.10404}
   }
   

3. Meike Nauta, Ron van Bree, and Christin Seifert. Neural Prototype Trees for Interpretable Fine-grained Image Recognition. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2021.
   BibTeX

   @inproceedings{Nauta2021_cvpr_prototree,
     author = {Nauta, Meike and van Bree, Ron and Seifert, Christin},
     booktitle = {{IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}},
     title = {Neural Prototype Trees for Interpretable Fine-grained Image Recognition},
     year = {2021},
     pages = {14933--14943},
     code = {https://github.com/M-Nauta/ProtoTree},
     doi = {10.1109/CVPR46437.2021.01469},
     file = {:own-pdf/Nauta2021_cvpr_ProtoTree_proceedings-version.pdf:PDF}
   }