Valentyn Melnychuk
PHD Candidate
Munich, Bavaria, Germany
Summary
👤
Senior🎓
Top SchoolValentyn Melnychuk is a PhD candidate at LMU Munich specializing in causal machine learning, causal inference, and probabilistic modeling, with nine years of applied research and engineering experience. He blends rigorous academic training (MSc in Data Science, top-ranked Bachelor in System Analysis) with hands-on implementation skills from roles at Fraunhofer and DataRoot, working across PyTorch, TensorFlow, Hydra, Mlflow and deployment tooling. His background spans semi-supervised learning, eye-tracking and behavior analysis, and production-focused data science—evidence of a practitioner who moves ideas from research to reproducible code. At Fraunhofer he built robust ML tooling and experiment pipelines, and earlier Java work gave him strong systems and backend foundations. Based in Munich, he brings a pragmatic research mindset that emphasizes causal questions and probabilistic rigor over black-box models.
9 years of coding experience
3 years of employment as a software developer
Ludwig Maximilian University of MunichIgor Sikorsky Kyiv Polytechnic Institute
English, German, Russian, Ukrainian
Github Skills (51)
markdown10
lifecycle10
incremental-learning10
machine-learning10
mlflow10
model-management10
dvc10
gitpod10
github-pages10
jekyll10
ai10
apache-spark9
python9
feature-matching9
matching8
Programming languages (4)
Github contributions (5)
Valentyn1997/xray
May 2019 - Jun 2020
Contributions:70 commits, 9 pushes, 5 branches in 1 year 1 month
Valentyn1997/seal-regression
Jun 2019 - Sep 2020
Linear regression with gradient descent implementation, based on PySEAL package
Contributions:22 commits, 4 PRs, 20 pushes in 1 year 3 months
gradient-descent-implementationregressionpythondescentlinear-regression
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