About

I image and analyze the human brain at mesoscopic resolution using 7 Tesla MRI, and develop the software that enables others to do the same.

My work is driven by a deep interest in how the human brain enables perception, especially vision and audition. Early on, I was drawn to magnetic resonance imaging (MRI) as a powerful, non-invasive tool for studying brain function—but I soon realized that its complexity demands a strong foundation in methodology. To extract meaningful insights, one must understand the physical and physiological artifacts inherent to the data and develop precise tools for analysis. This led me to pivot from application to methodology: since my PhD, I have focused on advancing ultra–high field MRI (7 T), both in acquisition and analysis. I design imaging protocols and build software that enable mesoscopic brain imaging—revealing new structure-function relationships and empowering others to ask deeper scientific questions.

Currently, I work as a "Researcher and Software Engineer" at Brain Innovation in Maastricht, The Netherlands, where I contribute to cutting-edge neuroimaging solutions that translate academic research into real-world applications. My academic journey has been deeply interdisciplinary—spanning neuroscience, MR physics, and software engineering. I hold a PhD in Cognitive Neuroscience from Maastricht University (2020), where I specialized in high-resolution brain imaging using anatomical, functional, and diffusion MRI, with a particular focus on the cortex, subcortex, and deep brainstem regions in living humans at 7 Tesla.

My work lies at the intersection of advanced MRI acquisition and next-generation neuroimaging analysis. I develop open source software that unlock the full potential of ultra–high field MRI, pushing the boundaries of how we visualize and understand the living human brain. Notably, I developed LayNii, one of the most widely used layer (f)MRI analysis tools, featuring advanced 3D geometry processing wrapped in an intuitive interface implemented in C++.

Recognizing the importance of accessibility and open science, I share my expertise through YouTube tutorials and online content—helping to rapidly disseminate my algorithms and analysis pipelines to a global audience.

In addition, I regularly publish peer-reviewed articles both independently and in collaboration with international research teams. I am a highly active member of the human brain imaging field, delivering invited talks, contributing to scientific conferences, and leading hackathon projects.

In summary, I’m passionate about building usable, impactful scientific tools and fostering collaborations that translate neuroscience from the lab bench to real-world impact. I carry this mission forward by combining scientific rigor with thoughtful software design, enabling researchers to visualize, analyze, and interpret brain data with precision and ease.

ORCID: 0000-0001-7761-3727