Mathias Goncalves
Software Developer at Stanford University
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolMathias Goncalves is a software developer in Boston with a decade of technical experience and a strong foundation in scientific programming, object-oriented development, test automation, and data science. Currently at Stanford, he has a track record building robust, reproducible neuroimaging tools and pipelines from his MIT work on large-scale analysis workflows and data standard integration. He is an active open-source contributor to prominent neuroimaging projects (nibabel, fMRIPrep, nipype), where he’s improved file-format compliance, surface processing, and command-line interfaces to increase reliability across diverse datasets. Comfortable bridging research and production, Mathias combines hands-on backend engineering with domain expertise in MRI data curation and visualization. His background in neurobiology gives him a rare ability to translate complex scientific requirements into maintainable software, and he often focuses on subtle data-integrity fixes that prevent downstream errors.
10 years of coding experience
5 years of employment as a software developer
Bachelor of Arts (B.A.), Biology - Neurobiology, Bachelor of Arts (B.A.), Biology - Neurobiology at Boston University
English, Spanish
Github Skills (18)
data-formats10
nipype10
python10
image-processing10
brain-imaging10
surf10
data-format10
nifti10
neuroimaging10
surface10
mri10
debug9
develop9
algorithm9
algorithms9
Programming languages (14)
Github contributions (5)
nipreps/fmriprep
Aug 2017 - Jan 2023
fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:24 releases, 180 reviews, 478 commits in 5 years 5 months
Contributions summary:Mathias made several code contributions focused on enhancing the fMRIPrep fMRI preprocessing pipeline, specifically modifying the processing of functional (fMRI) GIFTI files. This included refactoring surface processing, modifying metadata handling, and introducing new options related to surface generation, and handling of image orientation. These modifications aimed to improve the robustness and functionality of the workflow within the fMRIPrep project.
neuroimagingdiversetransparentpipelinefmriprep
nipy/nipype
Apr 2016 - Sep 2022
Workflows and interfaces for neuroimaging packages
Role in this project:Back-end Developer
Back-end DeveloperContributions:5 releases, 19 reviews, 410 commits in 6 years 6 months
Contributions summary:Mathias primarily contributed to the development of a dcm2niix interface within the nipype library. Their contributions centered around enhancing the interface to support additional compression levels, series selections and to handle the new NRRD export functionality and by refactoring and simplifying the codebase. Further commits indicate that the user was involved in fixing a test related to a new feature, indicating an active role in maintaining code quality.
workflowneuroimagingpythondata-scienceworkflow-engine
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.