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M. Nauta MSc (Meike)

About Me

I am a PhD Candidate at the Data Science group of the University of Twente, the Netherlands. My research interests include explainable artificial intelligence, deep learning, causal discovery and data mining.

Daily life is increasingly governed by decisions made by algorithms due to the growing availability of big data sets. Most machine learning algorithms are black-box models, i.e. they give no insight into how they reach their outcomes which prevents users from trusting the model. If we cannot understand the reasons for their decisions, how can we be sure that the decisions are correct? What if they are wrong, discriminating or amoral?
I aim to create new machine learning methods that can explain their decision making process, in order for users to understand the reasons behind a prediction. Those explanations enable the user to check for correctness, fairness and robustness, and can also be useful for knowledge discovery.

Expertise

Engineering & Materials Science
Convolutional Neural Networks
Decision Making
Deep Learning
Image Recognition
Neural Networks
Radiology
Mathematics
Image Recognition
Interpretability

Publications

Recent
Nauta, M., Hegeman, J. H., Geerdink, J., Schlötterer, J. , Keulen, M. V. , & Seifert, C. (2024). Interpreting and Correcting Medical Image Classification with PIP-Net. In S. Nowaczyk, P. Biecek, N. C. Chung, M. Vallati, P. Skruch, J. Jaworek-Korjakowska, S. Parkinson, A. Nikitas, M. Atzmüller, T. Kliegr, U. Schmid, S. Bobek, N. Lavrac, M. Peeters, R. van Dierendonck, S. Robben, E. Mercier-Laurent, G. Kayakutlu, M. L. Owoc, K. Mason, A. Wahid, P. Bruno, F. Calimeri, F. Cauteruccio, G. Terracina, D. Wolter, J. L. Leidner, M. Kohlhase, ... V. Dimitrova (Eds.), Artificial Intelligence. ECAI 2023 International Workshops - XAI^3, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, 2023, Proceedings (pp. 198-215). (Communications in Computer and Information Science; Vol. 1947). Springer. https://doi.org/10.1007/978-3-031-50396-2_11
Nauta, M. , & Seifert, C. (2023). The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers. In L. Longo (Ed.), Explainable Artificial Intelligence: 1st World Conference, xAI 2023, 2023, Proceedings (pp. 397-420). (Communications in Computer and Information Science; Vol. 1901 CCIS). Springer. https://doi.org/10.1007/978-3-031-44064-9_21
Nguyen, E. , Nauta, M. , Englebienne, G. , & Seifert, C. (2023). Feature Attribution Explanations for Spiking Neural Networks. In Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023 (pp. 59-68). IEEE. https://doi.org/10.1109/CogMI58952.2023.00018
Le, P. Q. , Nauta, M. , Nguyen, V. B. , Pathak, S., Schlötterer, J. , & Seifert, C. (2023). Benchmarking eXplainable AI: A Survey on Available Toolkits and Open Challenges. In E. Elkind (Ed.), Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 (pp. 6665-6673). (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2023-August). International Joint Conferences on Artificial Intelligence.
Nauta, M., Schlötterer, J. , van Keulen, M. , & Seifert, C. (2023). PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image Classification. Abstract from 2nd Explainable AI for Computer Vision Workshop, XAI4CV 2023, Vancouver, British Columbia, Canada.
Borys, K., Schmitt, Y. A. , Nauta, M. , Seifert, C., Krämer, N., Friedrich, C. M., & Nensa, F. (2023). Explainable AI in medical imaging: An overview for clinical practitioners - Saliency-based XAI approaches. European journal of radiology, 162, 110787. https://doi.org/10.1016/j.ejrad.2023.110787
Nauta, M. (2023). Explainable AI and Interpretable Computer Vision: From Oversight to Insight. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036555753

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Contact Details

Visiting Address

University of Twente
Drienerlolaan 5
7522 NB Enschede
The Netherlands

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Mailing Address

University of Twente
P.O. Box 217
7500 AE Enschede
The Netherlands