Welcome to the page of Dr. Tim Christian Kietzmann. I am a Researcher at the MRC Cognition and Brain Science Unit of the University of Cambridge and a member of the Lab of Prof. Niko Kriegeskorte. I investigate principles of neural information processing using tools from machine learning and pattern recognition, 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 for latest updates.

Research Interests

Cognitive Neuroscience meets Machine Learning. My main research focus is on 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 the world around us. Questions I ask include: What are the basic computational properties and representational transformations at the different stages of processing? What temporal dynamics govern visual processing and how does experience affect them? What is the role of overt visual attention in visual perception?

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

Twitter Feed

Just in case you were wondering what this #ScientistAndParent is up to lately...

How can we act on fine detail object information if higher-level visual cortex has large receptive fields? V4 may contain clusters that code high-acuity information about objects:
Work by Yiliang Lu, Wei Wang et al.

Our story now up in the @eLifeCommunity #scientistandparent series: Combining science and parenthood, and how the flexibility of academia can be a benefit when things turn out differently than 'planned' @DrAnneLaura https://t.co/QkbznOLZMy

I've had this experience over and over again:
1. I explain to non-academic friends how the scholarly publishing business works.
2. They assume they misunderstood me.
3. I explain again.
4. They assume I've made a mistake.
5. I explain again.
6. They can't believe we're this dumb. https://t.co/V4ppHpI4fG

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