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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. My main research aim is to understand dynamic information processing in the brain. Focusing mainly on vision, I am particularly interested in understanding the cortical mechanisms that allow us to robustly extract information from noisy sensory information. I ask how the brain learns robust representations from the statistical regularities in the world. What are the underlying computational mechanisms and representational transformations? What are the computational objectives that the visual system optimises for, and how do they shape neural representations? What temporal dynamics govern information processing and how does experience affect them?

I approach these questions by combining human neuroimaging with machine learning techniques (pattern recognition, and deep neural network models).

Newsfeed rss
Twitter Feed

What a great timing ... some students just asked me for recommendations regarding Python refresher/intro material and I just see that Microsoft just released a Intro to Python video series on YouTube yesterday: https://t.co/PzVqFN6fIa

Working from home with the institutional VPN turned off is a painful reminder of how cut-off the general public is from research output.

Recently I ran a workshop on course creation for new faculty, and in the process arranged a list of ~20 pieces of advice (maxims from books, articles, twitter). I'll now start posting them here 🙂

A thread collecting some resources for learning the maths behind comp neuro!
Especially useful if you've wanted more detail on our episode topics like generative models, deep learning, etc https://t.co/5uvZ4xaHnD

Any recommendations for a good NSFW image classifier w freely available code/repository? APIs are not feasible as we want to check more than 1.5 million images.

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