I apply tools from mathematics to questions in cognitive science. My current research interests are how people and algorithms process the arrow of time. Could new causal inference algorithms help to understand the human perception? Also, I am developing new psychophysical methods to perform robust experiments, e.g. novel experiments to objectively quantify causal perception. The PhD is jointly supervised by Felix Wichmann and the Max-Planck-Institute for Intelligent Systems and part of the DFG SFB 1233 ''Robust Vision'' .
I modeled the optics of the human eye with location dependent point spread functions in my master thesis. Previously, I implemented Deep Neural Networks.
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Meding, K., Schölkopf, B., Wichmann, F. A.
Perception of temporal dependencies in autoregressive motion
European Conference on Visual Perception (ECVP), 2019 (poster)
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Bruijns, S. A., Meding, K., Schölkopf, B., Wichmann, F. A.
Phenomenal Causality and Sensory Realism
European Conference on Visual Perception (ECVP), 2019 (poster)
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Goris, R., Henaff, O., Meding, K.
Representation of sensory uncertainty in macaque visual cortex
Computational and Systems Neuroscience (COSYNE) 2018, March 2018 (poster)
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Meding, K., Hirsch, M., Wichmann, F. A.
Retinal image quality of the human eye across the visual field
14th Biannual Conference of the German Society for Cognitive Science (KOGWIS 2018), 2018 (poster)
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Meding, K., Loktyushin, A., Hirsch, M.
Automatic detection of motion artifacts in MR images using CNNs
42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages: 811-815, March 2017 (conference)
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