Welcome to the page of Dr. Tim Christian Kietzmann. I am a Researcher and Graduate Supervisor at the MRC Cognition and Brain Science Unit of the University of Cambridge (line manager Prof. Niko Kriegeskorte). 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

I am incredibly excited about the new eLife feature #ScientistAndParent to which my family and I contributed.


Christmas is coming early this year: the @nvidia GPU grant program has gifted us with a brand new titan xp!


7 Questions about academic publishing

7 Questions about academic publishing - my take on the publication process, targeted at MSc students (printed ...

Looking forward to joining Darwin College as a Postdoctoral Research Associate!


Deep Neural Networks In Computational Neuroscience – preprint published

show all
Twitter Feed

Formally, a computer science department is the smallest set of researchers such that, for every researcher R, there exists a researcher S who believes R is not doing "real" computer science.

Important result from "artificial neuroscience" for neuroscientists: if a neuron happens to respond in a highly selective fashion to say cats-or Jennifer Aniston-that does not mean that it is more important in recognizing cats than nonselective neurons.

This might be my most exciting discovery @SciPyConf: MatLab to Python migration guide from @enthought. Also available as a PDF: https://t.co/LKZFL457ez

we are preparing our paper for @biorxivpreprint : Evolution of neocortical folding: A phylogenetic comparative analysis of MRI from 33 primate species

with @R3RT0 @ofgulban Pierre-Louis Bazin, Anastasia Osoianu, Romain Valabregue, Mathieu Santin, Marc Herbin

Having received a rejection letter this morning, I am happy to announce that I am at least making good progress in 3D printing my impostor syndrome...

Load More...