Jon Gorroño
Postdoctoral Research Fellow at Brigham and Women's Hospital
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolJon Gorroño is a postdoctoral research fellow at Harvard Medical School and Brigham and Women’s Hospital with 11 years of experience applying engineering and software development to biomedical imaging. He specializes in diffusion MRI, tractography and connectomics, blending deep expertise in computational neuroanatomy with a strong track record of producing robust tools and reproducible research. An active maintainer and contributor to major open-source toolkits (ITK, VTK, DIPY) he pairs back-end development and test automation with careful technical writing to improve code quality and documentation. His background spans commercial R&D for surgical planning and PACS, micro-CT acquisition, and web-based systems, giving him rare end-to-end insight from clinical imaging hardware to scientific software. Notably, he has driven testing and reliability improvements in visualization projects like FURY and expanded ITK’s coverage through targeted tests and module updates.
11 years of coding experience
12 years of employment as a software developer
Computational Neuroscience, Computational Neuroscience at University of WashingtonEngineer, Telecommunications, Medical Information Processing Systems, Engineer, Telecommunications, Medical Information Processing Systems at IMT AtlantiquefMRI Visiting Fellowship Program, fMRI, tractography, fMRI Visiting Fellowship Program, fMRI, tractography at The MGH/HST Martinos Center for Biomedical ImagingStatistical Analysis of fMRI Data, Statistical Analysis of fMRI Data at Johns Hopkins Bloomberg School of Public HealthCharles III University of Madrid (Universidad Carlos III de Madrid)Summer School, Biomedical Imaging, Summer School, Biomedical Imaging at Eidgenössische Technische Hochschule ZürichDrugs and the Brain, Drugs and the Brain at California Institute of TechnologyClinical Problem Solving, Clinical Problem Solving at UCSFExperimental Genome Science, Experimental Genome Science at University of PennsylvaniaIntroduction to Genetics and Evolution, Introduction to Genetics and Evolution at Duke UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Université de SherbrookeMaster's degree, Medical Physics, Master's degree, Medical Physics at Universidad Nacional de Educación a Distancia - U.N.E.D.Biomedical Image Analysis Summer School: Modalities, Methodologies & Clinical Research, Biomedical Imaging, Mathematics, Neuroimaging, Biomedical Image Analysis Summer School: Modalities, Methodologies & Clinical Research, Biomedical Imaging, Mathematics, Neuroimaging at CentraleSupelecEngineer, Telecommunications - Signal Processing and Communications, Engineer, Telecommunications - Signal Processing and Communications at Universidad del País Vasco/Euskal Herriko Unibertsitatea
Basque, Spanish, English, French, German
Github Skills (18)
c-language10
3d-graphics10
restructuredtext10
python10
image-processing10
testing10
rs10
itk10
scientific-visualization10
cprogramming-language10
documentation10
numpy9
code-formatting9
test-automation9
image-analysis8
Programming languages (21)
Github contributions (5)
InsightSoftwareConsortium/ITK
Sep 2018 - Jan 2023
Insight Toolkit (ITK) -- Official Repository. ITK builds on a proven, spatially-oriented architecture for processing, segmentation, and registration of scientific images in two, three, or more dimensions.
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:783 reviews, 528 commits, 631 PRs in 4 years 4 months
Contributions summary:Jon primarily focused on updating and testing the ITK (Insight Toolkit) library, a toolkit for processing and analyzing scientific images. Their contributions include updating various remote modules by bumping them to the latest commits. They also added and improved tests, particularly for the ResampleImageFilter, and performed style enhancements and code coverage improvements throughout the project. These changes were focused on testing existing functionality and expanding the features of the testing suite.
itksegmentationinsight-toolkitimage-analysismedical-imaging
dipy/dipy
Apr 2017 - Dec 2022
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
Role in this project:Technical Writer
Technical WriterContributions:464 reviews, 206 commits, 291 PRs in 5 years 8 months
Contributions summary:Jon primarily contributed to documentation improvements and corrections, focusing on fixing typos and formatting issues within the repository's documentation files, including reStructuredText (.rst) and Python example files. Their work involved correcting spelling mistakes, improving grammar, enhancing code block formatting, updating links and cross-references, and adding or modifying sections on coding style, dataset information, and the usage of tools like GitHub Actions. The user's edits spanned multiple files across various directories, consistently aiming to enhance the readability, clarity, and overall quality of the documentation.
3dimagingmachine-learningpythonsignal-processing
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