Javier Guaje
Mentor & Maintainer at Diffusion Imaging in Python
Greater Bloomington Area United States
Summary
👤
Senior🎓
Top SchoolJavier Guaje is a computer scientist and software engineer with 11 years of experience specializing in image and medical imaging analysis, machine learning, and scientific visualization. He mentors and maintains the FURY visualization library—contributing 300+ commits and pioneering PBR shader work and reusable actors—while also being a significant contributor to DIPY’s interactive visualization tools. His research at Indiana University produced measurable performance and accuracy gains in diffusion MRI pipelines and symbol rendering, and he has applied ML in industry to build NLP and computer vision products. Comfortable across the full stack, Javier combines rigorous academic training (PhD/MS, Indiana University) with practical open-source impact and a track record of mentoring new contributors through programs like Google Summer of Code.
11 years of coding experience
3 years of employment as a software developer
Master of Engineering - MEng, Computer Science, Master of Engineering - MEng, Computer Science at Universidad Nacional de ColombiaDoctor of Philosophy - PhD, Computer Science, 3.9, Doctor of Philosophy - PhD, Computer Science, 3.9 at Indiana University Bloomington
Spanish, English
Github Skills (17)
3d-rendering10
visualization10
shader10
python10
glsl10
computer-graphics10
neuroimaging10
medical-imaging10
vtk10
visualizations10
opengl10
tractography9
user-interface9
uid8
front-end-development8
Programming languages (6)
Github contributions (5)
fury-gl/fury
Sep 2019 - Aug 2022
FURY - Free Unified Rendering in pYthon.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:152 reviews, 202 commits, 40 PRs in 2 years 11 months
Contributions summary:Javier focused on extending the `fury-gl/fury` repository by implementing a diverse range of features. They added a new example to visualize a shader canvas, subsequently refactoring the example files by division. They also contributed to examples with parallax, sines and other shader experiments and built reusable actors such as square and cube and a function to generate surface. Finally, they implemented the PBR (Physically Based Rendering) features to a bunch of actors.
pythonrenderingscientific-visualizationscriptable-animationsgame-engine
dipy/dipy
Sep 2018 - Feb 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:Full-stack Developer
Full-stack DeveloperContributions:3 reviews, 18 commits, 6 PRs in 3 years 6 months
Contributions summary:Javier significantly contributed to the medical imaging library, specifically focusing on enhancing the interactive visualization capabilities within the Horizon application. Their work involved adding features such as ROI (Region of Interest) visualizations, including the display of binary images as contours, and integrating random color assignment for both tractograms and ROIs. They also made minor bug fixes, like updating broken links, and refactored and improved the Slicer and ROIs panels.
3dimagingmachine-learningpythonsignal-processing
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