Cognitive Modeling

Sarah Fabi, Dr. rer. nat.

E-Mail: sarah.fabispam prevention@uni-tuebingen.de

Personal website

 

 

 

 

Academic Career

  • 2022: Visiting scholar, Stanford University
  • 2021: Visiting scholar, University of California San Diego 
  • 2019–2021: Postdoctoral researcher, Neuro-Cognitive Modeling, University of Tuebingen
  • 2014–2018: Doctoral student, Biological Psychology, University of Tuebingen
  • 2013–2014: Master of Science, Psychology, University of Tuebingen
  • 2009–2013: Bachelor of Science, Psychology, University of Konstanz
  • 2011–2012: Exchange student, University of Barcelona, Spain

Publications

  • Hagendorff, T., Fabi, S., & Kosinski, M. (under review). Machine intuition: Uncovering human-like intuitive decision-making in GPT-3.5.
  • Raina, R., Monares, M., Xu, M., Fabi, S., Xu, X., Li, L., Sumerfield, W., Gan, J., &  Virginia R. de Sa. (2022). Exploring Biases in Facial Expression Analysis using Synthetic Faces. In NeurIPS Workshop SyntheticData4ML.
  • Fabi, S., & Hagendorff, T. (under review). Why we need biased AI - How including ethical and cognitive machine biases can enhance AI systems.
  • Fabi, S., Xu, X., & de Sa, V.R. (2022). Exploring the racial bias in pain detection with a computer vision model. Proceedings of the Annual Meeting of the Cognitive Science Society, 44.
  • Fabi, S., Holzwarth, L., & Butz, M.V. (2022). Efficient learning through compositionality in a CNN-RNN model consisting of a bottom-up and a top-down pathway. Proceedings of the Annual Meeting of the Cognitive Science Society, 44.
  • Fabi, S., Otte, S., Scholz, F., Wührer, J. Karlbauer, M., & Butz, M.V. (2022). Extending the Omniglot Challenge: Imitating Handwriting Styles on a New Sequential Dataset. IEEE Transactions on Cognitive and Developmental Systems.
  • Fabi, S., Otte, S., & Butz, M.V. (2021). Fostering compositionality in latent, generative encodings to solve the Omniglot challenge. In I. Farkas, P. Masulli, S. Otte, \& S. Wermter (Eds.), Proceedings of Artificial Neural Networks and Machine Learning -- ICANN 2021, Part II, 525-536. Springer (DOI).
  • Fabi, S., Otte, S. & Butz, M.V. (2021). Does Compositionality as a prior in Generative RNNs lead to efficient learning of temporal predictions?. Poster presented at the ICDL Workshop Spatio-temporal Aspects of Embodied Predictive Processing 2021.
  • Fabi, S., Otte, S., & Butz, M.V. (2021). Compositionality as learning bias in generative RNNs solves the Omniglot challenge. In International Conference on Learning Representations (ICLR) - Workshop Learning to Learn. (DOI)
  • Fabi, S., Otte, S., Wiese, J.G., & Butz, M.V. (2020). Investigating efficient learning and compositionality in generative LSTM networks. In I. Farkas, P. Masulli, & S. Wermter (Eds.), Artificial Neural Networks and Machine Learning - ICANN 2020, 143-154. Springer. (DOI, arXiv)
  • Hobbhahn, M., Butz, M.V., Fabi, S., & Otte, S. (2020). Sequence classification using ensembles of recurrent generative expert modules. In Proceedings of the 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - ESANN 2020, Bruges, Belgium, 333-338. (DOI)
  • Fabi, S., Weber, L.A., & Leuthold, H. (2019). Empathic Concern and Personal Distress depend on situational but not dispositional factors. PLOS ONE, 14(11), e0225102. (DOI)
  • Fabi, S., & Leuthold, H. (2019). Investigating empathy for pain toward racial in- and outgroup targets ­­­with ERPs and EEG oscillations. Poster presented at the 4th Workshop of Understanding Others - Integration of Social Cognitive and Affective Processes, Munich.
  • Fabi, S. (2018). How do we process pain in others? Investigating behavioral and neural correlates of empathy. Dissertation. (Link)
  • Fabi, S., & Leuthold, H. (2018). Racial bias in empathy: Do we process dark- and fair-colored hands in pain differently? An EEG study. Neuropsychologia, 114, 143-157. (DOI)
  • Fabi, S., & Leuthold, H. (2018). Racial bias influences on empathic information processing - An EEG study. Poster presented at the Social and Affective Neuroscience Society Meeting (SANS), New York.
  • Fabi, S., & Leuthold, H. (2018). Measuring empathic influences on perceptual and motor processing with ERPs, EEG oscillations, and response force. Poster presented at the Cognitive Neuroscience Society Meeting (CNS), Boston.
  • Fabi, S., Mackenzie, I.G., & Leuthold, H. (2017). Are empathic influences on information processing subject to racial bias? An EEG study. Poster presented at the 59th Conference of Experimental Psychologists (TeaP), Dresden.
  • Fabi, S., & Leuthold, H. (2017). Empathy for pain influences perceptual and motor processing: evidence from response force, ERPs, and EEG oscillations. Social Neuroscience, 12, 701-716. (DOI)