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Eneko Uruñuela, PhD
Machine Learning | Medical Imaging | Open Source Development
Eneko Uruñuela is a Biomedical Engineer with a PhD in machine learning for medical imaging, specializing in developing deconvolution algorithms for estimating neuronal-related activity from functional MRI data.
During his Master's degree in Biomedical Engineering, he focused on data analysis and bioinformatics, completing his thesis on deconvolution of fMRI signals at the BCBL.
Eneko has professional experience working on firmware testing systems for brain stimulation signals at Neuroelectrics, and developing algorithms for EEG data analysis to detect seizures in neonates.
His competencies include Python, Matlab, R language, signal processing, data analysis, inverse problems, and image processing, with additional experience in C++.
Currently, he is a Researcher PhD Student at the Basque Center on Cognition, Brain and Language and has previously held positions as a Teaching Assistant at Neuromatch Academy and various roles at Neuroelectrics.
To learn more about Eneko Uruñuela, visit his website at https://www.enekourunuela.com.
Highlights
I'm thrilled to announce that just three months into my new role, our team's paper has been accepted at MICCAI's ISLES challenge!
🚀 We've also been invited to give an oral presentation.
A huge thanks to our amazing team for making this possible. Excited for what's next!
🎉 Thrilled to share I've received the Alberta Innovates fellowship!
I'll be working on AI models for stroke care, focusing on personalized treatments & data privacy.
Excited to push the boundaries in health tech!
