Krug
Wiss. Mitarbeiter/-in
Dr.-Ing. Valerie Krug
Institut für Intelligente Kooperierende Systeme (IKS)
AG Artificial Intelligence Lab
AG Artificial Intelligence Lab
Universitätsplatz 2, Gebäude 29,
39106 Magdeburg,
G29-024
vCard
- pronouns: she/her
- spoken languages: English and German
Main Research Focus
- explainable Artificial Intelligence (XAI)
- analyzing and visualizing Deep Learning models (aka Introspection)
Further Interests
- visualizing and communicating science
(e.g. for exhibits, public talks)
Selected Publications:
- Neuroscience-Inspired Analysis and Visualization of Deep Neural Networks.
Valerie Krug.
Dissertation/PhD thesis, Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik, 2024.
[URL]
- Visualizing Deep Neural Networks with Topographic Activation Maps.
Valerie Krug; Raihan Kabir Ratul; Christopher Olson & Sebastian Stober.
In HHAI 2023: Augmenting Human Intellect. IOS Press, 2023. 138-152.
[URL] [github]
- Analyzing and Visualizing Deep Neural Networks for Speech Recognition with Saliency-Adjusted Neuron Activation Profiles.
Valerie Krug; Maral Ebrahimzadeh; Jost Alemann; Jens Johannsmeier & Sebastian Stober.
In: Electronics 10 (11), 1350, 2021.
[URL]
- Visualizing Deep Neural Networks for Speech Recognition with Learned Topographic Filter Maps.
Valerie Krug & Sebastian Stober.
In: Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2019.
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Neuron Activation Profiles for Interpreting Convolutional Speech Recognition Models.
Valerie Krug; René Knaebel & Sebastian Stober.
In: NeurIPS 2018 Interpretability and Robustness for Audio, Speech and Language Workshop (IRASL’18), 2018.
Education
- Since 2024: Postdoctoral Researcher at the AI Lab, OVGU
- 2019 - 2024: Researcher/PhD student at the AI Lab, OVGU
- 2016 - 2019: Researcher/PhD student at the Machine Learning in Cognitive Science Lab, University of Potsdam
- 2013 - 2016: Master of Science "Bioinformatics", University of Potsdam
- 2010 - 2013: Bachelor of Science "Biotechnology/Bioinformatics", Mittweida University of Applied Sciences
Below, you can see the classes I'm currently involved in.
- Deep Learning für Ingenieure ( Link zur LV im LSF )