Hamed Rad
Software Engineer at RAHAT Research Center
Innsbruck, Tyrol, Austria
Summary
🤩
Rockstar🎓
Top SchoolHamed Rad is a software engineer based in Innsbruck with nine years of experience building back-end web systems and applying machine learning to real-world problems. He leads development at ICTN while concurrently working as a machine learning engineer at RAHAT Research Center, where he applies deep learning to medical imaging and genetic data. His background in software engineering and an M.Sc. in Mechatronics give him a multidisciplinary edge for bridging algorithmic research and production services. Comfortable across the stack, he focuses on scalable back-end architectures and ML pipelines, and occasionally contributes to open-source data-prep tooling for machine learning. Colleagues rely on him for pragmatic solutions that translate complex models into maintainable systems.
9 years of coding experience
7 years of employment as a software developer
Master of Science (M.Sc.), Mechatronics, Master of Science (M.Sc.), Mechatronics at Azad University (IAU) - Tabriz Branch
Persian, Azerbaijani, English, Turkish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
machine-learning10
data-cleaning10
data-science10
python9
data-analysis8
documentation7
Programming languages (5)
Github contributions (5)
skrub-data/skrub
Oct 2018 - Oct 2018
Prepping tables for machine learning
Role in this project:
Data Scientist
Data ScientistContributions:6 commits, 5 PRs in 1 day
Contributions summary:Hamed primarily contributed to the project by making minor text adjustments and corrections within existing code files and documentation. These edits included fixing misspellings, punctuation, and capitalization in several example scripts and code comments. The user also made minor changes to documentation. The nature of their work involved improving clarity and readability, but did not demonstrate any core functionality development.
autoencoderdata-preprocessingdatadata-sciencetabular-data
hamedonline/ml-workflow
Oct 2021 - Jan 2023
A hands-on case study for demonstrating the stages involved in a machine learning project, from EDA to production.
Contributions:71 commits, 5 PRs, 45 pushes in 1 year 3 months
pythonproductionlearning-projectdata-scienceeda
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