Rafael Henriques
Assistant Professor at Instituto de Biofísica e Engenharia Biomédica - Institute of Biophysics and Biomedical Engineering
Lisbon, Portugal
Summary
👤
Senior🎓
Top SchoolRafael Henriques is an Assistant Professor and diffusion MRI specialist with 11 years of research and software experience bridging neuroscience, biomedical engineering, and open-source development. He earned a PhD from the University of Cambridge studying diffusion MRI microstructure and spent seven years as a postdoc at the Champalimaud Neuroscience Programme before moving to the Institute of Biophysics and Biomedical Engineering. Rafael contributes to flagship open-source projects like DIPY, where he implemented and documented diffusion kurtosis imaging (DKI) simulation tools used for multicompartmental modeling. He combines domain expertise in diffusion-weighted imaging with hands-on coding and reproducible research practices, enabling both method development and practical tools for the community. Based in Lisbon, he brings a rare mix of academic rigor and production-quality software contributions that accelerate computational neuroimaging.
11 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Diffusion MRI, Doctor of Philosophy (Ph.D.), Diffusion MRI at PhD University of Cambridge
Github Skills (4)
diffusion-mri10
python10
data-analysis10
machine-learning9
Programming languages (3)
Github contributions (5)
dipy/dipy
Mar 2015 - Jun 2021
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:
Data Scientist
Data ScientistContributions:41 reviews, 499 commits, 34 PRs in 6 years 4 months
Contributions summary:Rafael implemented new functions in the `dipy.sim.voxel.py` module for performing Diffusion Kurtosis Imaging (DKI) simulations based on the DKI model, specifically for performing multicompartmental simulations. They also refactored and improved the documentation and formatting of the existing DKI simulation functions. A new example script was added to demonstrate the use of the DKI simulation functions.
3dimagingmachine-learningpythonsignal-processing
RafaelNH/Free-water-elimination-DTI
Feb 2016 - Apr 2019
Reproduce the artice Hoy et al. 2014 Optimization of a free water elimination two-compartment model for diffusion tensor imaging. Neuroimage 103:323-33. doi: 10.1016/j.neuroimage.2014.09.053
Contributions:93 commits, 36 PRs, 37 pushes in 3 years 2 months
imagingtensor
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.