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For Psychologists:
Classically cognitive psychology theorises about experimental evidence in a qualitative way. More recently, however, there has been an increasing development of mathematical and computational models of experimental results. These models are often more clearly defined and more detailed than their qualitative counter parts. My aim is to develop such models for a broad range of psychological phenomena. However, as this objective can be best achieved in interaction with behavioural data, I also conduct experimental research.
I apply this computational approach to a broad range of topics and areas:
• Cognitive Neuroscience
• Visual Object Recognition
• Visual Attention
• Cognitive Neuropsychology
• Visual Affordances
• Social Exclusion
Typically my models are based on a neural computation framework. However, recently I began to explore the usage of agent-based modelling as well.
For Computer Scientists:
My area is part of Artificial Intelligence. However, in contrast to typical AI, I aim to understand human information processing by simulating evidence from experimental psychology. Typically, I use neural networks to design my models. However, recently, I began to explore the usage of agent-based approaches as well. My models are applied in the area of visual perception and object recognition (computer vision), but also in research into understanding social interactions.
For Engineers:
My area is part of computational engineering. However, in contrast to typical applications in this field, e.g. civil engineering, I try to simulate aspects of the brain and the resulting human behaviour. In order to constrain the structure of my models, I use a neural network approach. The data I aim to simulate is data from experimental psychology in the area of human vision.