Hi, I'm Eneko 👋

I have a PhD in machine learning for neuroimaging.

I want to make healthcare more accessible and affordable to everyone.

Recent publications

Cited by 191

Unraveling Hidden Patterns of Brain Activity: A Journey Through Hemodynamic Deconvolution in Functional MRI

(2024)

PyProximal-scalable convex optimization in Python

Journal of Open Source Software (2024)

Uncovering the Neural Correlates of the Urge-to-Blink: A Study Utilising Subjective Urge Ratings and Paradigm Free Mapping

bioRxiv (2024)

Individual variability in the relationship between physiological and resting-state fMRI metrics

bioRxiv (2024)

Bayesian Modelling Approaches for Breath-Hold Induced Cerebrovascular Reactivity

bioRxiv (2024)

Whole-brain multivariate hemodynamic deconvolution for functional MRI with stability selection

Medical Image Analysis (2024)

Hemodynamic Deconvolution Demystified: Sparsity-Driven Regularization at Work

Aperture Neuro (2023)

Conferences

A Multi-Subject Deconvolution Algorithm for the Analysis of Naturalistic fMRI Data

ISMRM Iberian Chapter 3rd Annual Meeting (2023)

Oral Scientific session, Best presentation

A Multi-Subject Deconvolution Algorithm for the Analysis of Naturalistic fMRI Data

ISMRM 32nd Annual Meeting & Exhibition (2023)

Best abstract, Suma Cum Laude Merit Award, Oral Scientific session

Exploring Tensor Decomposition as an Alternative to ICA for Denoising Multi-Echo fMRI Data

ISMRM 32nd Annual Meeting & Exhibition (2023)

A multi-echo low-rank and sparse method to estimate neuronal signal with less global signals bias

ISMRM Iberian Chapter 2nd Annual Meeting (2022)

Power Pitch

A multi-echo low-rank and sparse method to estimate neuronal signal with less global signals bias

OHBM Annual Meeting (2022)

Rica - Reports for visualizing and classifying ICA components of multi-echo fMRI

OHBM Annual Meeting (2022)

Blind estimation of neuronal-related activity in fMRI informed by co-fluctuations of brain regions

OHBM Annual Meeting (2022)

Talks

Unraveling Hidden Patterns of Brain Activity: A Journey Through Hemodynamic Deconvolution in fMRI

Advanced Medical Imaging Seminar Series - University of Calgary.

November 21st, 2024.

A Multi-Subject Deconvolution Algorithm to Analyze Naturalistic fMRI Data At The Finest Temporal and Spatial Resolution

ISMRM Workshop on Current Issues in Brain Function.

September 4th, 2023.

A Multi-Subject Deconvolution Algorithm for the Analysis of Naturalistic fMRI Data

ISMRM Iberian Chapter 3rd Annual Meeting.

July 4th, 2023.

A Multi-Subject Deconvolution Algorithm for the Analysis of Naturalistic fMRI Data

ISMRM 32nd Annual Meeting & Exhibition.

June 7th, 2023.

Multi-Subject Paradigm Free Mapping: A Promising Frontier for Analyzing Naturalistic fMRI Data

Cambridge Babylab, University of Cambridge, UK.

May 24th, 2023.

Featured projects

tedana

TE-dependent analysis of multi-echo fMRI

162

aroma

ICA-AROMA, as a Python package. A work in progress.

mapca

A Python implementation of the moving average principal components analysis methods from GIFT

rica

Rica (Reports for ICA) provides an app to visualize ICA components and perform manual classification in an interactive way

pySPFM

Python version of 3dPFM and 3dMEPFM

pyproximal

PyProximal – Proximal Operators and Algorithms in Python

My interests

Working on new deep learning projects.
Giving to the research community in Calgary .
Staying active.
Exploring new cities and learning from new connections.
Making the most of tools for thought .
Using AI to be more productive with daily tasks.

Let's chat