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 
I am incredibly excited about the new eLife feature #ScientistAndParent to which my family and I contributed.
https://elifesciences.org/interviews/24427a8f/tim-kietzmannChristmas 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_seeding7 Questions about academic publishing
7 Questions about academic publishing - my take on the publication process, targeted at MSc students (printed ...Twitter Feed
Inspired by everything I learned at @neurohackademy, and with the help of the @mrccbu open science committee, I prepared a list of resources that may be useful in transitioning to more open, reproducible and pythony science: https://t.co/CSvc7AoA3V
The largest multi-task data fMRI data set in the same subjects ever? Not clear, but it was a lot of work for sure! Maedbh King's work reveals a new functional map of the human cerebellum.
@ivryrich @diedrichsenlab @russpoldrack
https://t.co/jgNnoBTskd
Dear @CogCompNeuro, will the conference articles be automatically indexed by google scholar at some point? @KordingLab @KriegeskorteLab
Brown researchers teach computers to see optical illusions https://t.co/BMSRFDab1q via @BrownUniversity #clps
Quite proud of this one... https://t.co/5PLtIXzKjv
