I am Eneko Uruñuela, a PhD student at the Signal Processing in Neuroimaging lab developing denoising algorithms for fMRI. Learn about my contributions.
More specifically, I am currently working on methods for the spatiotemporal deconvolution of fMRI data (both single-echo and multi-echo fMRI) and tensor decomposition methods for the denoising of multi-echo fMRI data.
Side projects include (but are not limited to):
tedana: a library for denoising multi-echo fMRI data.
maPCA: a python implementation of the moving average Principal Component Analysis method from GIFT.
The physiopy suite: a set of tools to work on your physiological data as well as making it BIDS compatible.
I was also the chair of Brainhack Donostia 2020 and have been part of the organization since 2019.
You’ve stumbled upon my working notes. These notes are mostly written for myself: they’re roughly my thinking environment. If a note seems confusing or under-explained, it’s probably because I didn’t write it for you (or I just haven't finished it yet).
I’m sharing them publicly with the aim of making my work more accessible, with the hope it covers the void online conferences have created. I also believe these notes can be less intimidating than reading a paper and can serve as a starting point to know about my work.
Mind that there’s no index or navigational aids. To navigate these notes you’ll need to follow the links.
👋 Say hi via email or Twitter and visit my main personal site!