Welcome to the page of Dr. Tim Christian Kietzmann. I am an Assistant Professor at the AI department of the Donders Institute for Brain, Cognition and Behaviour (Radboud University), and a Senior 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 neuroscience, 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 fields of neuro-inspired machine learning and cognitive computational neuroscience.

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Twitter Feed

I'm hiring! Searching for a research assistant who likes mental health neuroscience & coding. Projects: computational psychiatry, inflammation, spectroscopy, maybe focused ultrasound stimulation. You'd get to join my great new PhD student @AliciaJ_Smith!

Taken together, the long-awaited cake (self-supervised learning) currently tastes much like the icing (supervised learning)! However, we’re just at the beginning of the revolution, with new cake recipes being created around the clock. (7/N)

On the very real possibility that doing all my teaching, writing, research, committee work, and mentoring on the same screen on the same computer in the same room is starting to mess with my mind #zoom #AcademicTwitter #WorkFromHome

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