Prof. Dr.
Katharina Dobs
Justus-Liebig-Universität Gießen
FB06 Psychologie und Sportwissenschaft
Otto-Behaghel-Straße 10
35394 Gießen
Short info
My research focuses on human visual recognition. I’m interested in how visual information is transformed until we recognize people, objects, their relationship to each other and the overall gist of a scene. I also investigate the functional organization of the human visual cortex and why some regions are specifically engaged in processing a single visual category and how those develop.
My long-term goal is to better understand how humans perceive and recognize the world around them in ever-changing natural environments. To this end, I combine recent advances in machine learning with human behavioral and neural data to provide a computationally precise account of how visual recognition works in humans.
Open Science
Multidimensional feature tuning in category-selective areas of human visual cortex.
bioRxiv, 2025-06.
Articles
Behavioral signatures of face perception emerge in deep neural networks optimized for face recognition.
Proceedings of the National Academy of Sciences, 120(32), e222064212.
Human-like face pareidolia emerges in deep neural networks optimized for face and object recognition.
PLOS Computational Biology (21.1), e1012751.
CNNs Reveal the Computational Implausibility of the Expertise Hypothesis.
iScience, 105976.
Using artificial neural networks to ask ‘why’ questions of minds and brains.
Trends in Neurosciences, 46, 72-88.
Deep neural networks optimized for both face detection and face discrimination most accurately predict face-selective neurons in macaque inferior temporal cortex.
Conference of Cognitive Compuational Neuroscience.
Idiosyncratic facial motions: Uncovering identity information in facial movements through a landmark-based analysis.
Journal of Vision, 24(10), 545-545.
Representations of dynamic facial expressions are shaped by both emotional and social features.
Journal of Vision, 25(9), .2123-2123
Models of vision need some action.
Behavioral Brain Science, 46:e405.
Artificial intelligence meets body sense: task-driven neural networks reveal computational principles of the proprioceptive pathway.
Signal Transduction and Targeted Therapy, 9(1), 171.
Core neural dimensions of functionally selective areas in the human visual cortex.
European Conference on Visual Perception (ECVP).
Efficient inverse graphics with a differentiable generative model explains robustness of perception to unusual viewing angles.
Conference of Cognitive Compuational Neuroscience.