Rodrigo Laiz
Researcher PHD Student at Helmholtz Munich
Munich, Bavaria, Germany
Summary
🤩
Rockstar🎓
Top SchoolRodrigo Laiz is a research-oriented PhD student and applied statistician with eight years of experience at the intersection of machine learning, neuroscience, and medical imaging. He has held research roles at leading institutions including Helmholtz Munich, EPFL and ETH Zürich, focusing on interpretability of self-supervised contrastive learning and data augmentation methods to improve fetal brain MRI segmentation. Trained in statistics and economics with computing minors across ETH Zürich, Universidad Carlos III and UC Davis, he combines strong probabilistic modeling skills with practical ML engineering. Rodrigo’s work spans academic collaborations on quantile factor models and climate-big-data topics as well as hands-on implementation of GAN-based augmentation and interpretability pipelines. Now based in Munich, he brings a rare blend of theoretical rigor and applied experimentation aimed at making complex models more transparent and clinically useful. Colleagues describe him as a curious, cross-disciplinary researcher who moves fluidly between statistical theory and code-driven validation.
8 years of coding experience
1 year of employment as a software developer
Bachelor's degree, Economics, Statistics, Computer Science, Bachelor's degree, Economics, Statistics, Computer Science at University of California, DavisCharles III University of Madrid (Universidad Carlos III de Madrid)Social Data Science, Computer science, Social Data Science, Computer science at Københavns Universitet - University of CopenhagenMaster of Science - MS, Statistics, Master of Science - MS, Statistics at ETH Zürich
English, Spanish
Github Skills (20)
python10
machine-learning10
gpu10
contrastive-learning10
pytorch9
numpy9
optical-flow9
neural-network9
deep-learning9
gpu-acceleration8
autograd8
tensorflow8
acceleration8
tensor8
image-registration7
Programming languages (2)
Github contributions (5)
gonlairo/CEBRA
Jun 2023 - Jan 2025
Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA
Contributions:1 PR, 45 pushes, 6 branches in 1 year 7 months
gonlairo/climate-change
Nov 2019 - Mar 2022
Contributions:3 pushes, 1 branch in 2 years 5 months
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