Gabriel Gavrilas
Intern - Data Analyst
Switzerland
Summary
👤
Senior🎓
Top SchoolGabriel Gavrilas is a data-focused software engineer and MS Computer Science candidate at ETH Zürich, with 11 years of hands-on experience building ML and data-processing systems. He has interned on NLP and machine translation research at TextShuttle and currently applies data-analytic skills at Universitätsspital Zürich, blending research rigor with practical deployment. His contributions to the DaCe (Data-Centric Parallel Programming) project demonstrate deeper systems-level expertise—implementing a TransientReuse transformation to optimize memory and fix edge-directed dataflow bugs. At AdNovum he prototyped federated learning pipelines and preprocessing/evaluation tooling, showing fluency across PyTorch, scikit-learn, and production workflows. Fascinated by machine learning’s real-world impact, he combines academic training with open-source engineering to bridge algorithms and efficient implementation.
11 years of coding experience
1 year of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at ETH Zürich
German, Romanian, French, English, Spanish, Italian
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
python10
scientific-computing9
parallel-computing9
cluster-computing9
networkx9
programming-language8
cuda4
fpga4
Programming languages (1)
Github contributions (5)
spcl/dace
Feb 2020 - Sep 2020
DaCe - Data Centric Parallel Programming
Role in this project:
Back-end Developer & Transformation Engineer
Back-end Developer & Transformation EngineerContributions:41 commits, 4 PRs, 10 comments in 7 months
Contributions summary:Gabriel contributed significantly to the DaCe (Data-Centric Parallel Programming) repository, focusing on implementing and refining dataflow transformations. They developed a `TransientReuse` transformation, aiming to optimize memory usage by reusing transient arrays. The user's work involved modifying code, and adapting the existing code base to improve functionality and the management of transients. They also fixed bugs related to edge redirection and data handling.
cudahigh-level-synthesisparallelhigh-performance-computingvivado-hls
targetsm/dace
Nov 2019 - Sep 2020
DaCe - Data Centric Parallel Programming
Contributions:157 pushes, 4 branches in 10 months
data-centricparallel-computingparallel-programmingparallel
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