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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.

https://elifesciences.org/interviews/24427a8f/tim-kietzmann

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

https://developer.nvidia.com/academic_gpu_seeding

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!

https://www.darwin.cam.ac.uk/

Deep Neural Networks In Computational Neuroscience – preprint published

http://biorxiv.org/content/early/2017/05/04/133504
Twitter Feed

“If you had infinite computational resources, you wouldn’t need [..] goals. [..] we have limits on what we’re able to compute, [..] we have to break the problem down into smaller parts because we can’t see all the way to the end” -- Tom Griffiths in https://t.co/2uwk777MmO 2017

Very nice write up on recent work on understanding generalization in deep learning, including a nice discussion of our recent @ICLR18 paper! https://t.co/Zs0TqvKZEf

We are hiring (again!). On the hunt for 2x new 3-year MRC funded postdocs. Please share widely! @camneuro @mrccbu @calmcbu
https://t.co/WeS4q9jOBm

By age 35, you should have executed 'rm -rf' against the wrong directory at least once.

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