Welcome to the page of Dr. Tim Christian Kietzmann. I am an Assistant Professor at the Donders Institute for Brain, Cognition and Behaviour (Radboud University), and a Research Associate at the MRC Cognition and Brain Science Unit (University of Cambridge). I investigate principles of neural information processing using tools from machine learning and deep learning, applied to neuroimaging data recorded at high temporal (EEG/MEG) and spatial (fMRI) resolution. Feel free to contact me with any questions or paper requests, and follow me on twitter (@TimKietzmann) for latest updates.
Research Interests
Cognitive Neuroscience meets Machine Learning. Our research group aims to understand the computational processes by which the brain and artificial agents can efficiently and robustly derive meaning from the world around us. We ask how the brain acquires versatile representations from the statistical regularities in the input, how sensory information is dynamically transformed in the cortical network, and which information is extracted by the brain to support higher-level cognition. To find answers to these questions, we develop and employ machine learning techniques to discover and model structure in high-dimensional neural data.
As a target modality, we focus on vision, the most dominant of our senses both neurally and perceptually. To gain insight into the intricate system that enables us to see, the group advances along two interconnected lines of research: machine learning for discovery in neuroimaging data, and deep neural network modelling. This interdisciplinary work combines machine learning, computational neuroscience, computer vision, and semantics. Our work is therefore at the heart of the emerging field of cognitive computational neuroscience.
Newsfeed 
New paper out in PNAS: Recurrence is required to capture the representational dynamics of the human visual system
https://www.pnas.org/content/early/2019/10/04/1905544116Twitter Feed
MS Wissenschaft 2019 finished its tour. We got data of 24.000 subjects driving by taxi or an autonomous car in the virtual town of Westdrive. Lots of work, even more fun.
https://t.co/lx1CvCbuF4
@hakeemjefferson @JakeMGrumbach since people seem to like the excerpt above, here's my whole peer review checklist - send it to your neighborhood journal editor! teach it to your grad students! leave copies scattered about academic conference venues! https://t.co/HaudsPaHbn
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I love this. Using deep networks to uncover previously hidden parts of Picasso's "The Old Guitarist".
To help recreate a lost Picasso painting, @UCL researchers used deep learning to recreate unseen parts of The Old Guitarist, one of Picasso’s most famous paintings from the blue period.
